Top Data & Analytics Jobs

Design, implement, and own reliable data solutions across design, manufacturing, and mission operations. Lead data architecture, migrations, ETL/replication, schema design, and optimizations. Partner with cross-functional teams, drive tradeoffs, prioritize work using data, mentor team members, and deliver production-ready data products.

The Data Engineer will design and implement data architecture, develop data ingestion pipelines, collaborate with stakeholders, and improve data-related processes.

Lead end-to-end migration of document-heavy legacy systems to cloud, converting unstructured records into analytics-ready formats, ensuring data quality and governance. Build and maintain MuleSoft integrations and APIs, apply data transformation (DataWeave), support Salesforce Data 360 implementation, and ensure lineage, metadata, and compliance while collaborating in Agile teams for phased cutovers and audit readiness.

Design, build, and maintain scalable cloud-native data platforms and pipelines (batch, streaming, near-real-time). Implement distributed processing (Spark), event-driven systems (Kafka), governance, security, observability, and support ML/analytics. Partner with cross-functional teams, optimize performance/cost, and mentor engineers while enabling production-grade data products.

Lead the architecture, development, and maintenance of scalable data pipelines and platform infrastructure supporting satellite operations, analytics, machine learning, and business decisions. Build data warehouses, lakehouse systems, data models, and dbt transformations; operate platforms using Databricks and related cloud services; and ensure data quality, reliability, security, governance, observability, lineage, and cost efficiency. Collaborate with product owners and multidisciplinary engineering teams on data requirements and platform capabilities.

Build and lead Harvey’s central data platform, including streaming and batch ingestion, CDC, Snowflake warehousing, orchestration, transformation frameworks, real-time processing, self-service tooling, and data quality, lineage, and governance. Establish secure patterns for PII, access control, retention, and multi-region data residency while setting technical direction and mentoring a growing team.

Build and lead Harvey’s central data platform, including streaming and batch ingestion, CDC, Snowflake warehousing, orchestration, transformations, real-time processing, and self-service tooling. Establish data quality, observability, lineage, governance, PII protection, access controls, and multi-region data residency. Own architecture and technical direction while setting standards, mentoring engineers, and partnering with Analytics, Data Engineering, Product, and Infrastructure teams.

Designs, develops, and maintains Databricks-based ETL pipelines, data lake architectures, datasets, and data quality processes supporting reporting, analytics, and AI/ML workloads. Maintains and migrates legacy SSIS and SQL Server systems, optimizes pipeline performance, and supports complex SSRS reporting. Collaborates with business users, analysts, and IT teams to define data requirements, troubleshoot issues, document solutions, and advance AI-assisted engineering practices.

Designs and maintains data models, databases, dictionaries, ETL workflows, and data quality processes. Partners with data owners and reporting teams to define requirements, resolve discrepancies, establish stewardship, and improve data sharing. Develops scalable PySpark and Python pipelines, optimizes SQL and Spark jobs, and implements AI/ML solutions using technologies including Snowflake and Oracle. Requires collaboration across teams, strong documentation, and adherence to data standards.

Designs, develops, and maintains Databricks ETL pipelines, data lake architectures, datasets, and data integrations supporting reporting, analytics, and AI/ML workloads. Troubleshoots and optimizes Databricks and SSIS processes, maintains legacy systems, implements data quality controls, and supports data warehousing. Maintains SSRS reports and collaborates with business users, analysts, and IT teams to deliver reporting solutions. Documents work, communicates technical information, and contributes to AI-assisted development practices.

Designs, develops, optimizes, and supports large-scale ETL/ELT data pipelines and transformation processes. Responsibilities include complex SQL, Python automation, XML processing, Linux and shell scripting, validation, monitoring, troubleshooting, and system integration support. The role collaborates with technical and nontechnical stakeholders, participates in Agile delivery, and communicates risks and recommendations. Java, AWS data services, relational databases, and reporting tools are preferred.

Build scalable data pipelines, ELT processes, infrastructure, and dimensional data models supporting internal analytics and customer-facing data products. Implement data quality monitoring, auditing, alerting, warehouse optimization, and governed semantic layers for AI and LLM-enabled analytics. Partner with technical and business stakeholders, improve data processes using AI, and deliver reliable metrics from diverse data sources.

Designs and owns production data schemas and models, builds AWS data infrastructure and artifact storage, and develops edge-to-cloud pipelines for robotic systems. The role also delivers ML infrastructure for training pipelines, dataset versioning, and model deployment. Candidates must have at least two years of AWS data infrastructure experience, strong distributed-systems modeling skills, ML infrastructure experience, and the ability to work across the stack. Travel to customer sites is required. Robotics, autonomy, industrial IoT, edge computing, and manufacturing experience are preferred.

Designs, develops, and supports SQL Server databases, SSIS ETL processes, Power BI reports, dashboards, datasets, and analytics platforms. Responsibilities include database administration, performance tuning, data integration, dimensional modeling, data governance, security, reporting standards, and business requirements gathering. The role also supports ERP integrations, data quality initiatives, enterprise analytics, and application enhancement projects while partnering with technical and non-technical stakeholders.

Designs and builds scalable, reliable, observable batch and streaming data pipelines and models. Partners with stakeholders on data integration, validates data quality, writes tests, participates in code reviews, documents solutions, troubleshoots production issues, and aligns technical work with business needs. The role requires strong programming, database, data modeling, governance, and Databricks knowledge, with preferred experience in Spark, AWS data services, CI/CD, testing, orchestration, and transformation frameworks.

Own the end-to-end cloud data platform, including ingestion pipelines, data warehousing, semantic models, governed reporting, and quality controls. Establish Git, CI/CD, testing, environment management, and data modeling standards. Lead Agile delivery, manage the backlog, automate workflows, and line-manage and mentor three engineers. Translate operational, clinical, and commercial needs into technical roadmaps and scalable data products.

Design, develop, and maintain scalable data platforms and pipelines. Build ETL/ELT workflows to ingest, parse, and process structured and unstructured data. Support scaling, monitoring, and operation of data stores, collaborate with cross-functional teams, and apply data engineering best practices for mission-driven projects.

Leads the design, development, and deployment of scalable cloud-native data pipelines for enterprise analytics and reporting. Establishes data engineering standards, governance, security, privacy, and compliance practices. Makes architectural decisions, mentors engineers, conducts reviews, translates business needs into technical solutions, and owns end-to-end data initiatives in an Agile environment.

Design, build, and optimize enterprise ETL/ELT pipelines, cloud data lakes, lakehouse solutions, data models, and semantic layers across AWS and Azure. Ensure data quality, security, performance, reliability, and governance while supporting analytics, reporting, and AI initiatives. Collaborate with product, engineering, IT, and business stakeholders to translate requirements into scalable data solutions, monitor pipeline health, troubleshoot issues, and improve data architecture and practices.

The Senior Data Engineer will design, implement, and manage data pipelines for real-time analytics and ML training datasets, ensuring efficient data flow and quality in a hybrid environment.

Own and scale the data platform powering ReadyOn's real-time labor OS. Design and operate batch and real-time pipelines, transformations, and data services (Python, PySpark, Airflow, Glue, Snowflake, Postgres). Build connectors, observability, data quality, and feature-store infrastructure while partnering with AI, backend, and product teams and providing technical leadership and mentorship.

The job involves leveraging AWS and Snowflake for data engineering tasks within a technology-focused company, requiring US residency.

Design, build, and maintain scalable ETL pipelines, data warehouses, and analytics infrastructure integrating EMR, revenue cycle, and operational data. Ensure data quality, HIPAA compliance, support reporting/BI, enable analytics, and collaborate with clinical, finance, and IT teams.

Design and build a medallion architecture using dbt and Microsoft Fabric, create and maintain data ingestion pipelines, and implement governance, lineage, documentation, and quality checks to support self-serve analytics while collaborating with cross-functional teams.

Design, build, and maintain cloud-based data pipelines and products to support analytics and ML. Create discoverable datasets, collaborate with embedded teams to capture system metrics, perform aggregation and visualization, develop production-ready Python/SQL/PySpark workflows, and implement monitoring, dashboards, and alerting to ensure data quality and system health.