Python And Sql Business Analytics Analyst Jobs

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

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: 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

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! About the team: The Customer Operations team is at the heart of Forma.ai's mission. This team has a direct impact on the growth of Forma.ai. They are results-driven and solutions-minded. The Customer Operations team works closely with our customers, helping them to understand and take advantage of all the features Forma.ai offers and ensuring that they get the most value from the platform. What you'll be doing: Reporting & Dashboarding Design, maintain, and enhance dashboards in BI tools (e.g., Looker Studio, Salesforce/HubSpot reports) to monitor marketing campaign performance, sales pipeline health, lead flow, and conversion metrics Automate recurring reports and implement self-serve analytics capabilities for GTM teams Data Analysis & Insights Analyze funnel performance from top-of-funnel marketing campaigns to bottom-of-funnel sales outcomes Provide regular insights into key KPI s like campaign ROI, customer acquisition cost (CAC), and attribution across channels Support A/B testing initiatives, sales activity analysis, and segmentation strategies Scripting & Automation Write Python and SQL scripts to extract, clean, and structure data from external sources (e.g., job boards, press releases, M&A feeds, web scraping APIs ) Build automated enrichment pipelines to augment CRM and marketing data with third-party insights (e.g., firmographics, hiring activity, technology stack, fun

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics & Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line. As a Data Engineer, you will: Work directly on new customer experiences built on one of the most advanced AI systems in the world Collaborate daily with researchers and engineers who are some of the best in the world at what they do Run implementations end-to-end and see initiatives through to real outcomes Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy You may be a good fit if you have: 5+ years of experience working on production-grade data processing systems Strong command of Python and SQL Experience with distributed data processing frameworks such as Apache Beam, Spark, or

About the Team The GTM Intelligence Solutions team builds the data and decision systems that help customer-facing teams take the right action at the right time. We combine product telemetry, commercial data, customer context, and field activity to identify account health and opportunity, recommend actions and use cases, deliver intelligence through field-facing products and agent workflows, and measure what happens next. We’re looking for a Data Scientist to help build the next generation of GTM intelligence at OpenAI. You will own a flexible portfolio of high-impact decision data products and work closely with Technical Success and other GTM teams to ensure the work drives better decisions. About the Role As a Data Scientist on GTM Intelligence Solutions, you will define and build the intelligence systems that help customer-facing teams prioritize accounts, identify risks and opportunities, choose interventions, and understand what worked. You will set the roadmap and methodology, build canonical features, ship reliable production workflows, monitor quality and adoption, and improve the systems using field feedback and business outcomes. This role combines hands-on technical depth with strong product and business judgment. You should be as comfortable writing production Python and advanced SQL, defining durable data contracts, and operating decision products as you are evaluating a ranking approach or designing an experiment. You will personally ship reliable first versions and partner with Analytics Engineering and Data Engineering when work requires shared infrastructure or additional scale. In This Role, You Will Set the roadmap and methodology for GTM intelligence and decision products, using deep stakeholder discovery to probe beyond stated requests, uncover the underlying decisions, workflows, constraints, and measures of success, and translate them into measurable systems. Own the full lifecycle of intelligence products, including feature definition, methodo

Roles & Responsibilities Displays structured problem solving, application of right tools & techniques to solve open ended problems, Creates productized analytics solutions or frameworks independently. Understand Business & product problems and come up with deep data backed solutions. Root cause analysis and Deep dive analysis of certain product problems Running and maintaining the reporting system, presenting insights at a weekly forum Building templates, dashboards in Power BI, Gsheets for operational and management reporting Data extraction as per business request for Ad hoc analysis Business analysis and understanding Evaluating metrics to be tracked as per business goals, exploring other available metrics for deeper understanding of product performance Work in a fast-moving environment, across multiple projects with varying levels of complexity and detailing Desired Skills and Experience: 3 - 5 years working with large data sets and conducting quantitative analysis Some understanding of Statistics and prior experience of building statistical models (e.g. hypothesis testing, product experimentation, A/B Testing, regressions). Excellent knowledge SQL and intermediate knowledge of data manipulation language such as R/Python Previous experience with working on ecommerce funnels, retention Ability to think through product and business metrics to assess product features Knowledge of business modelling and basic knowledge of financial metrics, would be a bonus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines Established expertise in designing new dashboards, identifying the right metrics, layout; displays proficiency in building dashboards on Power BI using best practices and intuitive Qualifications Bachelor’s in engineering, Computer Science, Economics, Statistics, or related discipline from a reputed institute ...........................

Become a part of our caring community The Financial Analytics Professional 2 manages data to support and influence decisions on day-to-day operations, strategic planning and specific business performance issues. The Financial Analytics Professional 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action. The Financial Analytics Professional 2 collates, models, interprets and analyzes data in order to identify, explain, influence variances and trends. Explains variances and trends in clinical and financial data and enhances modeling techniques to improve forecast accuracy. May possess financial or actuarial background. Understands department, segment, and organizational strategy and operating objectives, including their linkages to related areas. Makes decisions regarding own work methods, occasionally in ambiguous situations, and requires minimal direction and receives guidance where needed. Follows established guidelines/procedures. Use your skills to make an impact Required Qualifications Bachelor's Degree 1&#43; years SQL and Python experience Microsoft Office (Excel, Power BI, etc.) Experience in compiling, modeling, interpreting and analyzing data in order to identify, explain, influence variances and trends Explain variances and trends and enhance modeling techniques Experience in managing data to support and influence decisions on day-to-day operations, strategic planning and specific business performance issues Must be passionate about contributing to an organization focused on continuously improving consumer experiences Preferred Qualifications Business Intelligence, Financial, or Actuarial background Azure Databricks experience</

About Team: Financial Planning and Analysis” (FP&A) team works closely with the CFO, FP&A head, and all the other functions to enable and improve data-driven decision-making. The team enables financial planning, and allocation of funds, and uses structured problem-solving approaches along with a wide range of statistical / operations research techniques to create productized solutions for business teams to consume. Role: We are seeking to hire a talented Finance Professional for the FP&A team. This role offers a wide spectrum of responsibilities spanning from Financial and strategic planning, dynamic resource allocation framework for growth and P&L sustainability, driving efficiency charters across the P&L line items, performance management, business analytics and benchmarking with external companies. Responsibilities: Prepare monthly, quarterly and annual financial plans to be executed. Hold guardrails for investment to maximize topline growth Develop financial model for planning, budgeting, variance analysis and performance management Strategic Planning, AOP and LRP creation with thorough and detailed how-lists for topline and P&L line items Lead the MEC process with stakeholders from Business Finance and Controllership. Action upon the key risks and opportunities with agility Identify opportunities for efficiencies across the org and partner with respective teams to develop action plan to maximize the returns on investment for topline growth as well as cost optimization Leverage SQL to extract and manipulate financial data for analysis, Create and maintain dashboards and reports using SQL based tools Handle complex ad hoc request with a shorter turnaround time and supplement such request with appropriate analysis and insights for enabling business decision-making Assessment and dissemination of impact on business due to macro trends, benchmarking with national and international peer companies to identify the

The Opportunity The world of design is changing rapidly, and the Pro Design team is leading that transformation. We are the Adobe organization behind Illustrator, InDesign, and emerging experiences that connect creativity, collaboration, and AI. Our teams are reimagining what professional design looks like for the next decade - building intelligent, connected tools that empower creators and teams to move faster without sacrificing craft. We are looking for a Senior Business Data Scientist who is creative, analytical, and unafraid to question the status quo and shape the decisions that move key business metrics at scale. Join us and build Adobe’s future products! What you'll Do Map the user funnel and build the metrics, cohorts, and dashboards that Product and Growth rely on to see how users move across free, trial, and paid tiers—and pinpoint where they drop off. Dig into the hard questions (what drives activation, which behaviors predict retention and expansion) and build propensity models for conversion, upgrade, churn, and expansion that feed real-time targeting and in-product nudges. Find and size growth bets and work with Product to ship them. Set north-star, driver, and guardrail metrics with your partners, and stand up multivariate experiments across onboarding, paywalls, in-product prompts, and pricing. What you need to succeed Minimum Requirements: Bachelor's degree in a quantitative field (Statistics, Mathematics, Computer Science, Economics, Engineering, or similar) or equivalent practical experience. 5&#43; years of experience in data science, product analytics, or a similar quantitative role. Proficiency in SQL and Python (or R) for data manipulation, analysis, and modeling. Hands-on experience designing and analyzing A/B tests and interpre

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Data Science sits at the heart of how Coinbase builds products and makes decisions. We partner with Product, Engineering, and Design to shape roadmaps, understand our users, and move the company's bottom line through rigorous experimentation, analytics, and advanced modeling. As a Data Scientist on the Consumer team, you'll improve the customer experience across Coinbase's consumer products — including spot and advanced trading, yield, Coinbase One, international expansion, and new launches such as prediction markets and equities trading. You'll define key metrics, build measurement and causal frameworks, and translate insights directly into product strategy and shipped improvements. What you'll do: Drive analysis and deep dives on ambiguous business problems, delivering insights and recommendations that guide team decision-making Own a broad scope of data and metrics — from core logging to polished data visualizations Lead code reviews, contribute SQL and Python expertise, and maintain reliable ETL pipelines Uphold a high bar for statistical rigor, ensuring experimentation and causal analyses build genuine confidence with stakeholders Required Skills and Experience: BA/BS in a quantitative field (Math, Stats, Physics, CS, or similar) with 5+ years of relevant experience, or a PhD with 3+ years of relevant experience Proven track record of delivering impa

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. Are you passionate about helping organizations unlock the power of AI through modern data architecture? Snowflake is looking for a customer-facing Solution Engineer who combines strong technical depth with executive presence and a passion for innovation. In this role, you’ll partner with Sales to guide customers from raw data to real AI impact — architecting scalable solutions, delivering compelling demos, and influencing complex buying decisions across executive and technical audiences. Location: Candidate MUST be located in or near Atlanta. What You’ll Do Lead customer conversations on AI strategy and data modernization. Design and demonstrate scalable data and AI solutions using SQL and Python. Support enterprise Proof of Concepts from concept to value realization. Translate complex technical concepts into measurable business outcomes. Navigate objections and competitive dynamics in high-stakes sales cycles. Leverage AI tools to personalize demos, accelerate preparation, and enhance delivery. What You Bring Strong SQL proficiency and experience with modern data warehousing. Experience using Python for analytics or ML workflows. Familiarity with AI/ML concepts, including Generative AI and LLMs. Exceptional communication skills across technical and executive audiences. Abi

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. Are you passionate about helping organizations unlock the power of AI through modern data architecture? Snowflake is looking for a customer-facing Solution Engineer who combines strong technical depth with executive presence and a passion for innovation. In this role, you’ll partner with Sales to guide customers from raw data to real AI impact — architecting scalable solutions, delivering compelling demos, and influencing complex buying decisions across executive and technical audiences. Location: Candidate MUST be located in the Mid-Atlantic (Pennsylvania, DC, Virginia or West Virginia) What You’ll Do Lead customer conversations on AI strategy and data modernization. Design and demonstrate scalable data and AI solutions using SQL and Python. Support enterprise Proof of Concepts from concept to value realization. Translate complex technical concepts into measurable business outcomes. Navigate objections and competitive dynamics in high-stakes sales cycles. Leverage AI tools to personalize demos, accelerate preparation, and enhance delivery. What You Bring Strong SQL proficiency and experience with modern data warehousing. Experience using Python for analytics or ML workflows. Familiarity with AI/ML concepts, including Generative AI and LLMs. Exceptional communication skills