Top Data & Analytics Jobs

Lead and mentor multiple Databricks-focused data engineering teams, define engineering best practices and reusable frameworks, drive CI/CD and performance/cost optimization, build and support analytical and streaming pipelines, and collaborate with architects, product owners, and cross-functional partners to deliver high-quality data products.

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.

Lead design and implementation of Jane's customer data infrastructure: own event collection, pipelines, CDP tooling, schema governance, identity resolution, and attribution. Work cross-functionally with marketing, BI, product, and engineering to set standards, evaluate tooling (e.g., RudderStack), ensure privacy-compliant instrumentation, and build reliable, consistent data delivery to the warehouse.

Lead the BI function owning Azure-based BI infrastructure and data pipelines, write and optimize complex SQL, maintain Power BI reporting and revenue analytics, lead and mentor BI analysts, collaborate with Sales/Finance/Operations, and ensure data quality and documentation standards.

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.

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

Design, develop, and maintain databases and scalable data pipelines. Build stored procedures, triggers, and ETL processes; perform testing, tuning, security, and data quality work. Collaborate with developers and stakeholders, document architecture, review code, and support reporting and integrations to enable restaurant and customer-facing systems.

Develop and maintain Palantir-based ETL and data transformation pipelines using Python and TypeScript. Ingest and format structured and unstructured data, integrate with external APIs, collaborate with data scientists on data models, perform O&M on ETL, produce documentation, conduct tier-2 triage, and design UI elements and custom functions.

Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and cloud services. Develop transformation workflows, integrate diverse data sources, enforce data quality, monitoring, and observability. Leverage AWS (S3, Glue, Lambda, Redshift) and cloud warehousing; collaborate with data science, analytics, and business teams. Contribute to governance, security, and automation initiatives.

Design, build, and maintain large-scale batch and real-time data pipelines on GCP (BigQuery, Dataflow, Dataproc, Pub/Sub). Migrate legacy ETL to cloud-native architectures, optimize query and pipeline performance, enforce data governance and security, and implement automated CI/CD for deployments while collaborating with cross-functional teams.

Design and build scalable data architectures and ETL pipelines to support cloud migrations. Develop batch and real-time data processing, ensure data quality and security, monitor and optimize pipelines, troubleshoot migration issues, document processes, and collaborate with cross-functional teams within Agile frameworks.

Design, build, and maintain scalable data pipelines and infrastructure. Integrate large datasets and ML models into production, leverage cloud and big-data frameworks, monitor pipeline health, troubleshoot issues, and collaborate with data scientists and stakeholders while documenting solutions.

Build, maintain, and operate ETL/ELT data pipelines for an enterprise data platform. Support deployment via IaC, monitor and troubleshoot pipelines, run data quality checks, document processes, and collaborate with senior engineers to test and deploy features in a mission-critical government environment.

Design, build, and maintain scalable GCP data architectures and ETL/ELT pipelines (batch and streaming) using BigQuery, Dataflow, Apache Beam, Cloud Storage, and Pub/Sub. Implement performance tuning, data quality and governance, secure access controls under federal requirements, and automated CI/CD for deployments. Collaborate with data scientists and infrastructure teams to modernize legacy systems and optimize data models for mission use.

Design, build, and deploy production-grade data and AI solutions on Databricks. Create scalable data pipelines, APIs, and Databricks Apps, integrate LLMs/AI APIs, deploy to cloud, implement CI/CD and governance (Unity Catalog), debug full-stack issues, and provide hands-on technical guidance to clients.

Develop and maintain business intelligence reports, dashboards, and visualizations using BI platforms. Write SQL queries in Oracle and Databricks, support dimensional data models and data warehousing, gather reporting requirements, optimize query and report performance, and help manage documentation, version control, scheduled refreshes, and reporting enhancements. The role also supports AWS-based reporting solutions and collaboration with technical and business stakeholders.

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.

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, implement, and administer operational data flows: ingest, clean, enrich, transform, secure, and move mission-critical data. Perform exploratory data analysis, troubleshooting, and collaborate with customers to ensure compliant, reliable data pipelines.

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, 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.

Looking for a Data Engineer focused on data visualization with experience in handling real-world data and effective communication through data. Extra credit for skills in probabilistic classifiers and full-text search engines.

Serve as a senior technical lead for data engineering consulting: work with customers, design complex data models, write and review efficient code, resolve complex bugs, mentor engineers, lead cross-functional development, and plan/execute automated and performance tests to deliver high-quality data solutions.

Design, build, and optimize scalable Azure-based data pipelines and data warehousing solutions. Implement ETL/ELT, data cleansing, validation, batch and real-time processing, monitor and troubleshoot pipeline performance, ensure data governance and security, document data flows, and collaborate with analysts and stakeholders to deliver reliable analytics-ready data.

Leads enterprise data integration and engineering capabilities, including APIs, middleware, ELT pipelines, data governance, master data management, and cloud analytics platforms. Designs secure, compliant integrations across ERP, CRM, clinical, research, quality, finance, and commercial systems. Establishes architecture standards, data quality controls, monitoring, validation, and support processes while coordinating internal engineers, vendors, and business stakeholders. The role also provides technical leadership for trusted datasets, regulatory compliance, operational reliability, and commercialization readiness.