Top Senior Data Engineer Jobs in Providence, RI

Own and optimize data infrastructure and ETL/ELT pipelines using SSIS and Microsoft Fabric. Build and maintain SQL Server data warehouse staging, transformations, and lakehouse ingestion. Implement CI/CD, version control with GitHub, monitor pipeline health, troubleshoot data issues, document data flows, and translate stakeholder requirements into data engineering solutions that support BI reporting.

Seeking a Senior BODS Developer to develop and maintain complex BODS processes for data transformation. The role includes improving data quality using Information Steward and GAC/URAC techniques, collaborating with teams, creating documentation, and mentoring others.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Responsible for designing, developing, and maintaining scalable data pipelines and infrastructure, implementing data governance, and collaborating with teams to meet data needs.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Build and manage data pipelines, ETL workflows, and DAGs using dbt, Apache Airflow, Python, SQL, and Snowflake. Develop custom Airflow operators and hooks, perform data modeling and source-to-target mapping, and implement data quality and cleansing processes. Use cloud platforms, CI/CD, version control, and Snowflake utilities including Snowpipe, Tasks, Streams, stored procedures, and data sharing. Collaborate across teams, communicate insights, solve complex problems, and participate in on-call escalation.

Design, build, and optimize large-scale data pipelines, ETL processes, data models, and data warehousing solutions. Manage and tune databases (SQL and NoSQL), lead big data and cloud implementations (Snowflake, Fivetran, dbt, Airflow), apply DevOps and containerization for data workflows, and mentor junior engineers to deliver scalable data processing and actionable insights.

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.

Leads data engineering strategy, architecture, delivery, support, and lifecycle management for secure, scalable cloud and hosted data solutions. Collaborates with technical and business stakeholders to deliver complex datasets, establish enterprise data standards, manage data engineering teams, and oversee maintenance, change management, capacity planning, business continuity, disaster recovery, and regulatory security requirements. The role also evaluates third-party tools and supports Azure DevOps, SDLC, CI/CD, and technical innovation.

Design, build, and optimize scalable cloud data pipelines and infrastructure. Maintain and refactor SQL and ETL processes, automate data workflows, ensure data quality/security, and troubleshoot complex issues. Provide technical leadership and mentor junior engineers while collaborating with stakeholders to translate requirements.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

The Senior Data Engineer will design and scale cloud-based data platforms, ensuring quality and performance while collaborating with cross-functional teams to deliver actionable data solutions.

The Senior Data Engineer will develop data engineering solutions, manage ETL workflows, and establish a new data practice while collaborating with stakeholders.

The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

Design, build, and operate Alpaca's scalable data platform and lakehouse infrastructure. Build low-latency streaming and CDC ingestion, batch pipelines landing in Iceberg, and tooling for BI and AI consumers. Manage IaC, Kubernetes deployments, monitoring/incident response, and partner with DevOps and analytics teams to meet growing data requirements.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, build, and own end-to-end data systems and pipelines powering payments, fraud response, and reporting. Implement streaming and batch integrations, APIs, and workflow orchestration. Define data correctness with monitoring, alerting, and tests. Create reusable patterns and collaborate with stakeholders to clarify requirements and tradeoffs.

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.

Designs and delivers a global analytics platform supporting reporting, visualizations, self-service analytics, and embedded data products. Responsibilities include data collection and processing, semantic modeling, warehouse and pipeline development, query optimization, governance, analytics enablement, and stakeholder collaboration. The role provides actionable insights from complex travel data and builds integrated analytics applications using cloud platforms and business intelligence tools.

Designs and maintains Snowflake-based cloud data pipelines and lake architectures for asset-based finance and mortgage servicing analytics. Leads legacy-system migrations, ETL/ELT development, data validation, reconciliation, and financial integrity controls. Translates business requirements into Jira epics and user stories, supports project planning, testing, cutover, and go-live readiness, and coordinates with business, finance, operations, and technical stakeholders.

Design and scale Zip’s enterprise data and AI platform across batch, streaming, structured, and unstructured workloads. Build reliable pipelines, AI-ready data products, semantic models, vector and hybrid search, and RAG capabilities. Establish standards for modeling, testing, governance, security, observability, and automation. Partner with engineering, data science, product, and business teams while mentoring engineers and influencing platform architecture.

Design and build modern GCP lakehouse architectures, including Python and Spark pipelines, BigQuery ingestion, Kafka CDC, Delta Lake and Iceberg UniForm integrations, Delta Sharing endpoints, Snowflake and Databricks connectivity, data lineage, governed access controls, and semantic-layer alignment. Collaborate cross-functionally, troubleshoot full-stack issues, and deliver reusable data-sharing adapters and end-to-end data features.

Leads enterprise data engineering initiatives by designing and optimizing data pipelines, data lakes, warehouses, and analytics infrastructure. Uses Snowflake, Informatica, SQL, and related technologies to integrate diverse data sources, improve data quality, secure PII, and support analytics and data science teams. Establishes governance, monitoring, scalability, performance, and cost-efficiency practices while mentoring teammates and partnering with stakeholders on complex technical solutions.

Leads data and analytics engineering for Zero Trust maturity assessment and implementation measurement. Designs common data models, integrates and validates enterprise data, develops maturity and risk metrics, supports prioritization and gap analysis, and establishes data quality, lineage, traceability, and documentation practices. Partners with dashboard and automation specialists to streamline reporting and data refresh workflows.