Data Engineer in India

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

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

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects. Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks . As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks. As a hands-on technologist with an extensive data engineering background using Databricks , you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration. What you'll be doing: Design, build, test and maintain data pipelines (ELT), according to business and technical requirements. Implement secure pla

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: The Data Engineer is responsible for the design, development, and implementation of scalable data solutions across the Azure Databricks platform supporting AUNZ. This role focuses on building and maintaining data pipelines using Databricks (Unity Catalog, DABs, DLT), PySpark, and SQL, delivering enterprise-scale data transformation, and supporting Power BI reporting through well-modelled silver/gold layer datasets. The Data Engineer works closely with the Head of Data & Analytics to execute technical scoping and delivery against business requirements. What you'll be doing: KRA 1 Data Pipeline Development • Design, build, test, and maintain data pipelines (ELT) using Databricks, Delta Live Tables, and Databricks Asset Bundles, according to business and technical requirements. • Manage data workflows and orchestration; ensure accuracy and availability of all ELT processes. • Design and deliver silver/gold layer data models within the medallion architecture to support downstream reporting. KRA 2 Platform & Governance • Implemen

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: As a Data Engineer in the WPP Enterprise Data Group, you will be responsible for the design and implementation of scalable data solutions providing enterprise-scale data transformation across a broad range of projects. Your role will focus on delivering solutions that utilize large-scale data ingestion, processing, storage/querying, streaming, and batch analytics using Databricks . As part of a team, you will implement world-class solutions designed by our data architects. Your responsibilities will include estimating, designing, coding, testing, deploying, and ensuring scalability and performance on Azure using key technologies like Databricks. As a hands-on technologist with an extensive data engineering background using Databricks , you will be joining a group of Data Engineers who are passionate about building the best possible solutions for our business and endorse a culture of life-long learning and collaboration. What you'll be doing: Design, build, test and maintain data pipelines (ELT), according to business and technical requirements. Implement secure platforms

This is where your work makes a difference. At Baxter, we believe every person—regardless of who they are or where they are from—deserves a chance to live a healthy life. It was our founding belief in 1931 and continues to be our guiding principle. We are redefining healthcare delivery to make a greater impact today, tomorrow, and beyond. Our Baxter colleagues are united by our Mission to Save and Sustain Lives. Together, our community is driven by a culture of courage, trust, and collaboration. Every individual is empowered to take ownership and make a meaningful impact. We strive for efficient and effective operations, and we hold each other accountable for delivering exceptional results. Here, you will find more than just a job—you will find purpose and pride. Perform development work and technical support related to our data transformation and ETL jobs in support of a global data warehouse. Can communicate results with internal customers. Requires the ability to work independently, as well as in cooperation with a variety of customers and other technical professionals. What you'll be doing Development of new ETL/data transformation jobs, using PySpark and IBM DataStage in AWS. Enhancement and support on existing ETL/data transformation jobs. Can explain technical solutions and resolutions with internal customers and communicate feedback to the ETL team. Perform technical code reviews for peers moving code into production. Perform and review integration testing before production migrations. Provide high level of technical support, and perform root cause analysis for problems experienced within area of

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

Data Engineer II — Pune, India. Apply via Workday.

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. Staff Fullstack Engineer - Data Products An overview of this role As a Staff Fullstack Engineer - Data Products , you will help build GitLab's in-product insights on top of the Data Insights Platform and the GitLab Knowledge Graph. You will be the technical anchor across reporting dashboards, inbound graph ingestion, and outbound data delivery, helping turn software delivery data into reliable and actionable intelligence for customers and internal teams. This is a strong fit if you want to work in a 0 to 1 space where you can shape what gets built, make early architectural choices, and guide work from specification through produc

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. Staff Fullstack Engineer - Data Products An overview of this role As a Staff Fullstack Engineer - Data Products , you will help build GitLab's in-product insights on top of the Data Insights Platform and the GitLab Knowledge Graph. You will be the technical anchor across reporting dashboards, inbound graph ingestion, and outbound data delivery, helping turn software delivery data into reliable and actionable intelligence for customers and internal teams. This is a strong fit if you want to work in a 0 to 1 space where you can shape what gets built, make early architectural choices, and guide work from specification through produc

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. Intermediate Fullstack Engineer - Data Products An overview of this role Data Products integrates GitLab and third-party software development lifecycle data, and builds the dashboards, APIs, and data products that turn it into reliable, interoperable intelligence for customers and internal teams. You'll work across the stack, contributing to frontend experiences, backend services, APIs, and AI-enabled workflows. This is a hands-on product engineering role. You'll develop features, learn how we build and operate large-scale data systems, and work closely with Senior and Staff Engineers to deliver secure, reliable, and performant s

Data Engineering – Technical Lead About Us: Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners. About the Role: This position requires someone to work on complex technical projects and closely work with peers in an innovative and fast-paced environment. For this role, we require someone with a strong product design sense & specialized in Hadoop and Spark technologies. Requirements: 4 to 8 years of experience in Big Data technologies. The position Grow our analytics capabilities with faster, more reliable tools, handling petabytes of data every day. Brainstorm and create new platforms that can help in our quest to make available to cluster users in all shapes and forms, with low latency and horizontal scalability. Make changes to our diagnosing any problems across the entire technical stack. Design and develop a real-time events pipeline for Data ingestion for real-time dash- boarding.Develop complex and efficient functions to transform raw data sources into powerful, reliable components of our data lake. Design & implement new components and various emerging technologies in Hadoop Eco- System, and successful execution of various projects. Be a brand ambassador for Paytm – Stay Hungry, Stay Humble, Stay Relevant! Skills that will help you succeed in this role: Fluent with Strong hands-on experience with Hadoop, MapReduce, Hive, Spark, PySpark etc.Excellent progr

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: Build systems for collection & transformation of complex data sets for use in production systems Collaborate with engineers on building & maintaining back-end services Implement data schema and data management improvements for scale and performance Provide insights into key performance indicators for the product and customer usage Serve as team's authority on data infrastructure, privacy controls and data security Collaborate with appropriate stakeholders to understand user requirements Support efforts for continuous improvement, metrics and test automation Maintain operations of live service as issues arise on a rotational, on-call basis Verify whether data architecture meets security and compliance requirements and expectations .Should be able to fast learn and quickly adapt at rapid pace. java/scala, SQL, Minimum Qualifications: Bachelor's degree in computer science, computer engineering or a related field, or equivalent Experience 6+ years of progressive experience demonstrating strong architecture, programming and engineering skills. Firm grasp of data structures, algorithms with fluency in programming languages like Java, Python, Scala. Strong SQL language and should be able to write complex queries. Strong Airflow like orchestration tools. Demonstrated ability to lead, partner, and collaborate cross functionally across many engineering organizations Experience with streaming technologies such as Apache Spark, Kafka, Flink. Backend experience including Apache Cassandra, MongoDB and relational databases such as Oracle, PostgreSQL AWS/GCP Solid hands on with 4+ years of experience. St

Job Description: Data & Analytics Engineer (3-4 Years Experience) : 100% Remote Job Title: Data & Analytics Engineer Experience: 3-4 years Location: Remote Employment Type: Full-time Team: Data Engineering & Analytics About the Role Eltropy is a digital conversations platform for credit unions and community financial institutions in the US. The Data Engineering & Analytics team builds the AWS data pipelines and customer-facing dashboards that power analytics across the platform. We are looking for a Data & Analytics Engineer with 3-4 years of experience who can own dashboard delivery end to end along with the pipelines behind it. The ideal candidate learns fast, builds product context quickly, listens well, and collaborates effectively across product, engineering, DevOps, and customer-facing teams. Key Responsibilities Own dashboard changes end to end in QuickSight and ThoughtSpot - new metrics and filters, SPICE refresh management, internal-to-production promotion, and post-release validation. Build and maintain batch and streaming ETL pipelines on AWS using Glue (PySpark), S3, Redshift, and Airflow (MWAA) DAGs. Write and optimize Redshift SQL; debug query performance, connection contention, and data mismatches across sources. Support near-real-time ingestion (Kafka/MSK CDC → Glue Streaming → S3 → Redshift). Investigate customer-reported analytics discrepancies (Jira/support tickets), root-cause them in the data, and communicate findings clearly to support, product, and engineering. Set up and respond to pipeline monitoring - CloudWatch metrics and alarms, monitoring DAGs, refresh health - and participate in incident triage and RCA. Develop deep product knowledge: understand what each metric means to our credit union customers and translate product changes into data model and dashboard updates. Ensure data quality, validation, and consistency across systems. Required Skills & Qualifications 3-4 years of experience in data engineering and/or