Data Engineer Jobs

Data Engineer-6336 itD is seeking an experienced Data Engineer to build and modify high-complexity data pipelines, monitoring, and alerting systems supporting a legal-focused infrastructure team. The ideal candidate will bring deep expertise in SQL, Python, ETL/data pipelines, and data warehousing , along with a proven track record of leading complex, cross-functional data engineering initiatives from planning through delivery. Location: Remote, with preference for candidates based in California and ideally the Bay Area. Candidates open to occasional onsite work in San Francisco should indicate this in their skills matrix. Contract: 3Months Pay Rate: depending on experience and market rate. We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities Build and modify high-complexity ETL and data pipelines to efficiently extract, transform, and process data from large-scale datasets. Develop and maintain monitoring and alerting systems that proactively identify data, infrastructure, and workflow issues. Design data warehousing solutions and optimize queries and pipelines for large-scale data processing. Collaborate with attorneys, data scientists, engineers, and other technical and non-technical stakeholders to understand data requirements, sources, dependencies, and timelines. Lead end-to-end data engineering initiatives across cross-functional teams, including planning, documentation, stakeholder coordination, system design, and execution. Identify potential data and system issues early and implement solutions that improve reliability, efficiency, and operational visibility. Communicate technical concepts and project status clearly and concisely to both technical and non-technical audiences. Internal Responsibilities Attend regular internal practice community meetings. Collaborate with your itD practice team on indu

What is PerfectServe? PerfectServe is a leading provider of clinical communication and physician scheduling solutions in the health IT space. The company was founded in 1997 and has grown steadily since then, with a notable jump after several major acquisitions were announced in 2019. PerfectServe now has 400+ employees, 30,000+ customers — spanning medical practices, hospitals, and health systems — and $100 million+ in annual revenue. PerfectServe’s mission is to accelerate speed to care by optimizing provider schedules and routing communications — including messages, pages, calls, and alerts — to the right place at the right time in any care setting. By facilitating real-time information sharing, building better schedules, and automating important clinical workflows, we believe we can help our customers advance patient care and improve the well-being of their clinicians. Leading analyst firms like Gartner® and KLAS Research have consistently validated our approach: In 2026, PerfectServe was named highest in execution and furthest in vision in the Gartner Magic Quadrant™ for Clinical Communication and Collaboration — the clear segment leader. PerfectServe also received two Best in KLAS awards in 2026 — one for physician scheduling and another for ambulatory clinical communications. That makes for 11 Best in KLAS awards over the past 9 years. At PerfectServe, you'll have a unique opportunity to join a collaborative team with decades of experience that finds new ways to delight our customers every day. This involves consistent efforts to stay on the cutting edge of product development, which includes everything from implementing AI in new and existing solutions to brainstorming with customers about novel workflows. But you don't have to be in product to make in impact — everybody at PerfectServe contributes to important work that moves the business forward. If you're looking for a well-established, tech-forward company full of smart people doing meaningful work

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About AlphaSense: AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination. In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent requi

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We are looking for Data Engineering interns who are excited to help scale the systems and pipelines that power decision-making at Figma. As an intern on our data team, you will partner with engineers and analysts to design and build reliable datasets, ensure data quality, and make Figma's data more accessible across the company. This internship will be based out of our San Francisco or New York Hub. What you'll do at Figma: Build, test, and document data pipelines that bring product or business data into Figma’s data warehouse Help design foundational datasets that are trusted, well-documented, and easy to use Optimize pipelines for performance and scalability as Figma grows Partner with cross-functional teammates to understand data needs and deliver solutions Contribute to the tools and practices that make working with data at Figma easier With support from a manager and mentor, you’ll own a scoped project from problem definition through implementation, testing, documentation, and sharing the results. Some projects you could work on: Develop new ETL jobs to integrate product or business data into our warehouse Improve the performance and reliability of core pipelines Build reusable datasets that support experimentation, product and business analytics, or cross-functional stakeholders Document and simplify complex data workflows for broader use We'd love to hear from you if you have: Experience coding in Python or a similar language and writing SQL queries Experience building or working with dat

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer Manager, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. Mentor and guide engineers, fostering knowledge sharing and best practices. What we are looking for? 8+ years of industry experience in data engineering. Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Data modelling and modern data platform design concepts Building and maintaining data platforms in Azure/AWS or GCP Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders.

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is seeking an accomplished Principal level Data Engineering Solutions Specialist (Openflow and Iceberg/Polaris) to drive sales execution for our ingestion workloads. This is a strategic role that works closely with the broader field organization to ensure the successful customer adoption of Snowflake’s Data Engineering and Data Lake capabilities. Responsibilities: Achieve pipeline generation and revenue targets for allocated accounts and/or territory on a quarterly and annual basis by developing a sales strategy in the allocated territory with a target account list Execute tailored sales plays to capture market opportunities in Data Engineering, helping customers optimize their use of Snowflake's platform. Work directly with customers to understand their Data Engineering needs, communicating insights to inform Snowflake’s product roadmap and ensuring alignment with customer requirements. Become an expert in Snowflake’s Data Engineering and Data Lakehouse capabilities and provide executive-level insights to customers and partners, guiding strategic discussions that emphasize the value of Snowflake’s Data Engineering capabilities. Work with our Account Executives, Sales Engineers, Leadership and Field CTOs to drive customer engagements from discovery and qualificati

About Dot Collective We are a new generation consultancy based across UK and EU and founded on the premises of the engineering excellence and empowering people to make an impact. We work with all modern tech stacks and typically run agile scrum on all our projects. About you Are you passionate about data and its transformational powers? Do you like being able to make a huge difference in a limited period of time? We might be just the right place for you. Your key skills and capabilities: · Implementing cloud-native data platforms · Engineering scalable and reliable pipelines · Good knowledge of distributed computing with Spark · Understanding of cloud architecture principles and best practices · Hands-on experience in designing, deploying, and managing cloud resources · Excellent python and SQL skills · Agile ways of working · Experience in cloud automation and orchestration using tools such as CloudFormation or Terraform · Monitoring and performance tuning of cloud-based applications and services Nice to haves: (MLOps): Model Deployment & Serving – Deploy and manage ML models using MLflow, Azure ML, SageMaker, or similar, ensuring scalability and performance. Monitoring & Retraining – Set up model drift detection, performance monitoring, and automated retraining ML Pipelines & CI/CD – Automate end-to-end ML workflows We expect you to have some knowledge about how to architect, design, develop, deploy, and operate a data platform. Our promise to you We will always see you as a human being and will do our very best to support your needs and wellbeing – well-designed co-working and collaboration spaces, remote working patterns that work for you, parenting leave, sabbatical

About StarRez StarRez is the global leader in student housing software, providing innovative solutions for on and off-campus housing management, resident wellness and experience, and revenue generation. Trusted by 1,400+ clients across 25+ countries, StarRez supports more than 4 million beds annually with its user-friendly, all-in-one platform, delivering seamless experiences for students and administrators. With offices in the United States, Australia, the UK, and India, StarRez blends the robust capabilities of a global organization with the personalized care and service of a trusted partner. The Role You have an uncanny knack for problem solving and you have a sharp product mindset. Our engineers are involved in all aspects of the software design process and create high-performing, scalable, and secure products. You’ll work alongside cross-functional teams to design right-size solutions that power a new market-leading Analytics platform. As a Data Engineer at StarRez, you will play a critical role in building and scaling the foundations of our Analytics & Data Platform. You’ll design and maintain reliable, secure, and scalable data pipelines and models that power a new generation of reporting, insights, and data-driven products across the StarRez ecosystem. This role sits at the intersection of data, product, and engineering. You will work closely with Data Analysts, Full-Stack Engineers, and Product teams to translate customer and business requirements into robust data solutions - enabling everything from standardised dashboards to advanced analytics and embedded intelligence. You are hands-on, pragmatic, and comfortable working in a fast-evolving environment where you’ll help shape both the technical platform and the operating model as we scale. What you’ll be doing Build and maintain scalable data pipelines to ingest, transform,

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services ( MS Azure, GCP preferred) , ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms. Successful ca

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? 2-5 years: Data Engineer Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Minimum of a bachelor's

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers. What You’ll Do As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers. What You’ll Do As a Data Engineer at Brex, you will be a core contributor in transforming raw data into actionable insights for various departments across the organization. You'll collaborate closely with Data Scientists, Software Engineers, and business units to create efficient data models, pipelines, and analytics frameworks that drive the business forward. You also play a leading role in the design, implementation, and maintenance of Core Data tables, our high-quality, curated data source for a

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. The Team Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business question