Top Data Engineer Jobs

Build and maintain scalable GCP-based data pipelines, ETL/ELT processes, and data models. Support migrations from legacy systems, enable ML integrations, enforce data quality and lineage, document Terraform modules, implement CI/CD across environments, and provide production support and performance tuning within Agile teams.

Designs, develops, and optimizes enterprise data pipelines, ETL processes, data models, databases, and healthcare analytics solutions. Supports database administration, performance tuning, security, high availability, disaster recovery, deployments, and data governance. Collaborates with analysts, data scientists, application developers, and stakeholders to deliver reliable data infrastructure for AI, machine learning, business intelligence, and population health initiatives.

Build and maintain scalable batch and streaming data pipelines for large and semi/unstructured data to support reporting, data science, ML training/execution and search analytics. Evaluate and deploy data technologies, collaborate with architects, data scientists and business partners, and handle coding, testing, deployment, monitoring, documentation and automation in an Agile environment.

Design and lead scalable ETL pipelines and data integration solutions, consolidate varied sources into centralized data warehouses, optimize SQL and Python data processing, mentor engineers, and collaborate with cross-functional teams to deliver compliant, high-performance data products and analytics capability.

Design, build, and operate enterprise-grade, cloud-native data platforms and scalable ETL/ELT pipelines for analytics and ML. Collaborate with cross-functional teams to implement data models, ensure performance, security, governance, and support production data solutions in Agile environments.

Design, execute, and support end-to-end data migration into SAP S/4HANA: extraction, transformation, validation, reconciliation, and cutover. Use LTMC/SLT/LVM and SQL to migrate and validate master and transactional data, collaborate with functional teams, troubleshoot issues, and document migration processes.

Design, build, test, and maintain ETL/ELT data integration pipelines and data architecture. Perform data mapping, profiling, quality remediation, and support BI/analytics by partnering with business and technical teams. Provide full lifecycle support, documentation, and continuous improvement in a hybrid agile environment.

The Data Engineer will develop and implement data pipelines, manage ETL processes, and work with big data in a collaborative team environment.

Design, build, and operate scalable ETL/ELT pipelines and data platform capabilities to support analytics, AI/ML, and product needs. Lead technical designs, mentor engineers, implement DataOps/CI/CD and observability, ensure data quality/governance/security, and optimize performance and cost across cloud-based data systems.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest from third-party APIs, optimize columnar formats, support ML initiatives, consult with stakeholders, and provision AWS/on-prem infrastructure with Terraform.

Designs, builds, and maintains scalable ETL/ELT pipelines, data workflows, integrations, and curated Silver and Gold data assets. Supports analytics, reporting, machine learning, and operational applications through batch and streaming processing. Responsibilities include data ingestion, transformation, validation, quality management, automation, documentation, and performance optimization across enterprise data platforms. Partners with cross-functional teams, modernizes data processes, and mentors junior engineers.

Design and own Ceresti’s end-to-end data architecture, including secure raw-data storage, validated file and API ingestion, Postgres pipelines, and curated analytics layers. Establish governance for HIPAA-protected data, data quality, lineage, observability, and access controls. Build ML feature tables and embedding capabilities, collaborate on data contracts, support Agile delivery, and mentor engineers on SQL and data-system design.

Design, build, and optimize end-to-end data pipelines and dataflows, integrate with AWS, maintain schemas/data dictionaries, provide Tier 3 support, collaborate with stakeholders and product teams, document architectures, and support off-hours deployments. Ensure data governance, scalability, and production readiness while working primarily on-site in a cleared defense environment.

Design, build, and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and cloud-based data platforms. Optimize systems for performance, reliability, security, and cost while implementing monitoring, governance, and data quality practices. Collaborate cross-functionally with data scientists, analysts, engineering, and product teams to deliver reliable data solutions and improve the data ecosystem roadmap.

Build and maintain scalable data pipelines, ETL/ELT processes, data lake and warehouse infrastructure, and data platform tools. Develop cloud-based infrastructure using AWS and Terraform, optimize processing for reliability and cost, and implement monitoring, logging, governance, quality, and security practices. Collaborate with data scientists, analysts, autonomy engineers, and product teams to deliver reliable data solutions.

Design and build scalable data lakes, warehouses, and lakehouse architectures. Implement Python ETL/ELT pipelines, orchestrate workflows with Airflow, ingest from third-party APIs, optimize columnar file formats, support ML initiatives, and consult stakeholders to translate business goals into data architecture roadmaps.

Design, build, and maintain scalable data ingestion, transformation, and delivery pipelines across data warehouses, big data, and cloud platforms. Partner with stakeholders to implement data products, enforce governance and quality, support MLOps, and provide technical guidance to junior team members.

Design and develop scalable data solutions and tooling to enable AI and advanced analytics across Azure hardware and software stacks. Identify opportunities for AI-driven impact, build data platforms and visualizations, and collaborate with engineers, data scientists, and program managers to improve efficiency, quality, and operational insights.

Design, develop, and maintain Customer Data Platform solutions and data pipelines to create unified customer profiles, manage identity resolution, enable audience segmentation and activation, ensure data quality and governance, and support integrations with marketing, CRM, and cloud data systems.

Design, build, and maintain ETL/ELT pipelines and API integrations to ingest, cleanse, transform, and analyze infrastructure and cloud data. Produce analytics, dashboards, and executive reports; automate workflows and support near-real-time processing. Follow SDLC/DevOps practices (Git, CI/CD), ensure data governance, quality, lineage, and support incident, release, and compliance activities.

Designs and implements cloud-first, event-driven data solutions and ETL pipelines for data warehouses (Snowflake/Oracle). Leads architecture, CI/CD, QA, and Agile delivery; mentors teams; builds scalable backend systems using AWS, APIs, and automation tools. Ensures project delivery on time and within budget while advising senior management on technical strategy.

The Senior Data Engineer will design and maintain data pipelines, manage a Snowflake environment, establish data quality, and lead data initiatives across teams, influencing company-wide technology decisions.

Designs and maintains ETL pipelines, data architectures, databases, data models, and master data management solutions. Analyzes, profiles, cleans, and validates complex datasets; establishes data quality standards; and develops automated data management processes. Partners with architects, data stewards, and business stakeholders to improve data integrity and support business requirements. Communicates insights through reports and presentations while using cloud, database, streaming, CI/CD, and data modeling technologies.

Design and optimize the enterprise data warehouse and ELT pipelines (batch and real‑time). Integrate Databricks, CRM, and external systems into a governed, observable data platform. Drive automation, cost optimization, and monitoring; mentor junior engineers; and partner with Analytics, Ticketing, and Marketing to deliver scalable data solutions that support reporting and ML initiatives.

Design, build, and maintain scalable data pipelines, client integrations, and data models to support reporting, analytics, and AI/ML. Ensure data quality, monitoring, and reliable ingestion of healthcare (FHIR/HL7, EHR) and claims data. Collaborate with product, engineering, and AI teams to enable downstream products and analytics.