Top Data & Analytics Jobs

Develop, validate, and maintain Power BI reports and dashboards using DAX and Power Query. Extract, clean, and analyze data with SQL, Excel, Python and VBA to support supplier quality metrics (PPAP, CRV, Run at Rate, QPR). Gather requirements, enable drill-down reporting, schedule refreshes, deploy reports to production, and act as SME for supplier quality systems (SPPS, SQMS, SCMS). Hybrid role requiring in-office presence three days weekly.

As a Sr. Lead Data Engineer, you'll collaborate across teams to develop technical solutions, lead developers, and utilize big data technologies and cloud services to support data transformations.

Lead Data Engineer designs, develops, tests, implements, and supports cloud-based data solutions. Collaborates with agile teams, mentors engineers, builds streaming and batch pipelines using big-data and cloud technologies, and ensures performant, well-tested code.

Lead data and software QA for enterprise data platforms: define testing strategy, build automated test frameworks, validate ETL/ELT and data transformations, run data quality checks and reconciliations, test APIs and data products, analyze datasets with SQL to find defects, drive root-cause resolution, participate in Agile ceremonies, and mentor team members to improve quality practices.

Lead design, build, and optimization of large-scale real-time and batch data ingestion and transformation pipelines. Integrate enterprise systems (SFDC, NetSuite, Workday), ensure data quality, observability, and reliability, and enable analytics/AI workflows. Architect solutions using Airflow, dbt, Python, Kafka, Snowflake, apply DevOps/CI-CD practices, mentor global teams, manage multiple projects, and align data engineering initiatives with product and business stakeholders.

As a Quantitative Developer, you'll innovate and enhance quantitative methods, develop custom tools, maintain data pipelines, and collaborate with researchers for advancing investment strategies.

Own and operate the iMData platform: design and build Databricks-based ETL pipelines using PySpark and medallion architecture, create gold-layer star schemas, migrate assets from Synapse to Databricks, implement CI/CD and Terraform IaC, ensure data security and observability, mentor junior engineers, and collaborate with stakeholders and ML engineers to deliver production-grade analytics and AI-ready data.

Design and implement scalable ETL/ELT pipelines for structured and unstructured data, ensure data quality for bot training and real-time decisions, integrate data with conversational AI platforms, monitor and maintain voice bot systems, implement logging/monitoring, optimize data flows, and collaborate with AI/ML, DevOps, and compliance teams.

The Data Migration Engineer migrates customer data into SaaS products, ensuring data quality and business continuity while collaborating with teams and managing customer requirements.

The role involves operational support for data warehouse systems, optimizing pipelines on AWS, managing CI/CD processes, and collaborating on data transformations.

Design, build, and maintain cloud-native, low-latency data pipelines and streaming solutions (Kafka, Spark, Flink) for telecom telemetry. Support observability, CI/CD, and IaC (Terraform/CloudFormation), mentor junior engineers, and enable near-real-time AI analytics and large-scale data integration for network visibility and reliability.

The Senior Data Engineer will architect AI infrastructure, design high-performance data systems, manage AI pipelines, and collaborate with cross-functional teams. Responsibilities include implementing data architecture best practices and providing documentation and leadership in data orchestration.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

As a Junior Data Engineer, you will assist in designing ETL/ELT workflows, maintain Python and SQL codebases, debug data pipelines, document processes, and collaborate with product teams on technical solutions.

The Data Engineer will build and maintain data platforms, deploy pipelines, monitor transformations, and collaborate with Data Scientists and DevOps.

The job involves building responsive web dashboards, advanced data visualizations, and analytics tools for unmanned aircraft systems, requiring a deep understanding of UI/UX design and data presentation.

The Principal Data Engineer will lead the design of data frameworks, mentor teams, implement MDM solutions, and ensure data quality across environments.

As a Data Engineer, you will design scalable data platforms, lead a skilled engineering team, collaborate on product development, and adopt engineering excellence principles within Agile frameworks.

The role involves migrating on-premises databases to AWS, developing Python scripts for data processing, and building AWS data pipelines. Responsibilities include supporting application teams, data modeling, and ensuring system efficiency.

The Data Engineer II will design and implement scalable data pipelines, collaborate with stakeholders, ensure data quality, and support analytics by utilizing cloud platforms and big data technologies.

The Data Engineer designs data architectures and pipelines, supports analytics teams, solves complex data challenges, evaluates tools, and mentors team members.

Lead design, build, and maintain scalable data pipelines and infrastructure using Azure Databricks, ADF, and SQL Server. Develop OLTP and dimensional models, integrate Salesforce and SaaS sources, implement batch and real-time processing, enforce data governance and CI/CD, troubleshoot performance, mentor team members, and drive improvements to reduce technical debt and improve cost and performance.

Build, operate, and optimize data platforms and pipelines (Snowflake, Azure ESB). Manage ETL, data migrations, ingestion, quality, and analytics tools (Cognos, Tableau). Collaborate with IT and business stakeholders, enforce data governance, support regulatory and cybersecurity requirements, and provide advanced support and system integration for banking APIs.

Design, build, operate, and support ETL/ELT pipelines, integrations, and curated datasets across enterprise systems (Salesforce, Deltek, Autodesk, Azure, Microsoft Fabric). Implement data models, orchestration, API-first services, data quality, governance, and monitoring to support BI, reporting, AI/ML, and secure data delivery.

Lead architecture and delivery of SoFi's data platform: build scalable data pipelines, drive cloud-native and AI-enabled tooling, enforce governance and security, mentor senior engineers, and support production on-call.