Top Senior Data Engineer Jobs

Lead design and delivery of Databricks-based Lakehouse solutions and end-to-end data engineering projects. Build and optimize ETL, streaming and batch pipelines, integrate cloud and on-prem systems, mentor team members, support pre-sales, and ensure governance, security, and platform performance.

As a Senior Data Engineer, you'll define data ontology, collaborate with teams, design data pipelines, and optimize data infrastructures to support analytics for Yahoo Mail.

Freelance Senior Data Engineer to implement and support Adobe Experience Cloud solutions (CJA, Launch, Journey Optimizer, Adobe Analytics). Design and maintain tracking, data pipelines, and data orchestration; work with CDPs for ingestion and activation; validate data quality; troubleshoot implementations; document data flows; collaborate with engineering, analytics, and business teams. Short-term remote contract (US only, excluding NM and HI).

Design, build, and operationalize complex data pipelines and products to support analytics and AI/ML. Analyze and transform source data, enforce data governance/security/quality, resolve high-complexity incidents, mentor team members, and partner with business stakeholders to deliver reusable, scalable data platform capabilities.

Design, build, and support scalable data platforms and pipelines (ETL, warehousing, APIs) using DBT, Snowflake, and SQL. Collaborate with architecture, security, and application teams, build CI/CD, provide escalated on-call support, mentor staff, and deliver data solutions for the bank.

Build and operate scalable data ingestion, transformation, and connector frameworks; design and maintain a knowledge-graph-based data fabric; normalize and vectorize enterprise data for LLM/AI workflows; implement governance, lineage, access controls, and secure APIs to serve ML/agent pipelines.

Design and maintain data models, build and optimize data pipelines and database infrastructure, integrate data with BI tools, ensure data quality and governance, troubleshoot performance and downtime, and collaborate with stakeholders to deliver reliable analytics and reporting.

Design, build, and optimize large-scale Databricks/Spark/Delta Lake data pipelines and Redshift data platforms. Implement ETL/ELT patterns, ingest telemetry and behavioral data (Matomo, FullStory, Pendo), improve performance and observability, provide L2/L3 production support and RCA, and mentor engineers while shaping data architecture and best practices.

Design, build, and maintain enterprise-scale data platforms and scalable ETL/ELT pipelines. Develop and operationalize data transformations in Palantir Foundry, debug logs, troubleshoot issues, and convert varied data into usable formats. Guide cross-functional teams, support platform scaling, monitoring, and operations, and apply PySpark/Spark SQL for analytics and reporting to support mission-driven use cases.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze massive structured and unstructured data to support enterprise analytics, ML, and reporting. Ensure reliable, performant production data platforms with troubleshooting, documentation, and orchestration.

Lead design and build of a client-facing analytics platform using Microsoft Fabric. Develop and maintain Fabric pipelines and notebooks, design lakehouse and dimensional models, optimize Power BI semantic models, enforce SDLC/CI-CD practices, ensure SLA reliability, and mentor team members while delivering scalable, client-focused analytics.

Design, build, and maintain cloud-based engineering data platforms and production pipelines. Create trusted analytics datasets, data models, validation rules, and semantic layers to support engineering, reporting, and AI-enabled insights. Partner cross-functionally to optimize performance, correctness, scalability, and cost for large-scale semiconductor test, manufacturing, and engineering data.

Design and develop scalable data architectures and pipelines across on-prem, cloud, and hybrid platforms. Build data warehouse and analytics solutions, perform data wrangling and discovery, mentor engineers, and assist in project planning and estimation to enable data-driven business insights.

Manage and develop data systems and architectures for the NC3 digital environment; perform ETL in cloud environments, build and query relational/non-relational databases, conduct advanced analytics and modeling, develop dashboards and data quality tools, and support DoD interoperability and data strategy.

Design and build scalable data pipelines for Investment Data Standard and knowledge graph, implementing data quality controls and collaborating with cross-functional teams.

Design, build, and optimize low-latency streaming analytics pipelines; develop time-series models, real-time APIs and visualizations; operationalize online ML inference and monitoring; deploy services with Docker/Kubernetes on cloud; implement observability, governance, and mentor engineering teams.

Lead Data Engineer partners with product, architecture, and engineering to design, build, and operate scalable data solutions. Responsibilities include translating product requirements into data designs, building ETL/ELT pipelines, optimizing data storage and flow, implementing data cleansing and automation, ensuring data quality and compatibility, guiding architectural patterns, estimating project scope, and mentoring teams while staying current with emerging data technologies.

Build instrumentation and batch/streaming ETL/ELT pipelines and REST API integrations to generate audience and trigger data for CRM/marketing automation. Ensure data quality, monitoring, and reliability at scale while collaborating with CRM, campaign, and operations teams.

Design, build, and optimize scalable GCP data pipelines and ingestion frameworks, develop BigQuery semantic layers and ELT/ETL workflows, implement automation, observability, and CI/CD, support data governance and quality, mentor engineers, and partner with stakeholders to deliver enterprise healthcare analytics solutions.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze massive structured and unstructured data to support enterprise analytics, machine learning, and reporting. Ensure reliable, performant, and cost-effective production data platforms.

Lead design and scaling of ELT pipelines and analytics schemas on Snowflake. Build Looker views, CI/CD automation, and orchestration workflows (Prefect/Airflow). Ensure production reliability with monitoring (Datadog, Monte Carlo), partner with cross-functional teams, and provide technical leadership including code reviews, testing, and end-to-end ownership of data integrity and platform trustworthiness.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Implement streaming solutions, workflow orchestration, and ensure reliable, performant, and cost-effective production data platforms.

Design, build, and operate large-scale Hadoop-based data pipelines and analytics platforms. Ingest, transform, and analyze structured and unstructured data to support analytics, ML, and reporting. Ensure reliability, performance, and cost-effectiveness in production; troubleshoot, document, and collaborate on data engineering workflows.

Design, build, and operate large-scale batch and streaming ingestion pipelines, medallion/lakehouse layering, identity resolution and golden-record consolidation, data-quality gates and reconciliation, source-to-canonical mappings and crosswalks, schema enforcement, and observability for client onboarding and production data flows.

Lead the data platform team owning dbt projects, CI/CD, and Snowflake infrastructure. Architect scalable onboarding for new sources, enforce data quality via tests and contracts, review designs, prioritize roadmap, partner with stakeholders, and grow engineers while advancing AI/agent integration.