Top Data & Analytics Jobs

Lead design and implementation of scalable cloud data platforms and ETL/ELT pipelines using PySpark/Databricks, Delta Lake, and Snowflake. Optimize Spark workloads, enforce data governance, support AI/ML (including RAG and Agentic AI), manage data federation with Starburst, mentor engineers, and engage stakeholders in an Agile environment to deliver enterprise-scale analytics solutions.

Support development and maintenance of data pipelines, cloud-based data platforms, and analytics solutions. Build and test ETL/ELT processes, develop scripts and queries (Python, SQL, PySpark), support AWS/Azure environments, implement CI/CD and Git workflows, monitor and troubleshoot pipelines, perform data validation/QA, document processes, and collaborate with stakeholders while growing technical skills.

Lead the architecture and technical direction of a cloud data platform spanning infrastructure, Databricks, CDC streaming, pipelines, data products, developer experience, and governance. Resolve cross-team technical challenges, establish platform standards, influence roadmaps, drive adoption, mentor senior engineers, and lead complex multi-squad initiatives with minimal direction.

Build complex ETL pipelines, databases, datasets, and data-quality processes using Python, SQL, Databricks, and cloud technologies. Develop Tableau and Power BI dashboards, operationalize data for mission decision-making, and collaborate with security and Agile teams. Apply CI/CD and DevSecOps practices to automate pipelines and validate models. Communicate analytical findings clearly while supporting cybersecurity, compliance, and operational insights for federal clients.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.

Build, implement, and support enterprise data and ETL systems across the full development lifecycle. Conduct systems analysis, design data warehouse and cloud solutions, provide operational support, manage risks, and implement security controls. Collaborate with business and technology stakeholders, resolve complex technical issues, establish development standards, and mentor junior analysts. The role requires expertise in AbInitio, AWS orchestration tools, multiple data platforms, Python, PySpark, Unix scripting, and banking technology.

Design, build, and maintain scalable ETL/ELT pipelines and data platforms to ingest, parse, and process structured and unstructured data. Collaborate with cross-functional teams to deploy, monitor, and operate data solutions, convert diverse data formats, and support analytics, reporting, and real-time streaming use cases. Follow version control practices and meet security and clearance requirements.

Design, build, and maintain scalable data pipelines and platforms for analytics. Develop scripts to parse and convert structured and unstructured data, implement ETL/ELT workflows, collaborate with cross-functional teams, use version control, and support platform scaling, monitoring, and operations on mission-driven projects.

Lead design, development, and operationalization of enterprise-scale data applications and pipelines. Build scalable ETL/ELT workflows for structured and unstructured data, drive data architecture and migration efforts, optimize Informatica ETL, work with relational and cloud data stores, support CI/CD and DevOps, and ensure monitored, reliable data platforms to enable analytics and mission outcomes.

The Lead Data Engineer will architect and develop reporting solutions, integrate AI, analyze complex datasets, and mentor team members to enhance data-driven decision-making.

The Senior Data Engineer will build data pipelines and infrastructure, modernize legacy systems, and ensure data reliability for analytics at ABCorp.

Build and own data pipelines, models, quality checks, dashboards, and visualizations for manufacturing and test data. Partner with optical, manufacturing, and quality engineers to create reliable data solutions, improve pipeline performance and cost, and support engineering and leadership decisions. Establish software engineering practices for data systems, guide technical direction across distributed sites, and mentor other engineers.

Designs, builds, and operates production ETL and ELT pipelines, data models, validation, reconciliation, monitoring, and documentation. Replaces legacy processes with tested, version-controlled solutions; supports an Amazon Aurora migration; and prepares reliable datasets for reporting, analytics, and AI initiatives. Partners with engineering, architecture, reliability, database, and business teams, translates ambiguous requirements into technical solutions, makes independent architectural decisions, and mentors other engineers.

Design, build, and maintain data lakes, data warehouses, and end-to-end data pipelines for a multi-tenant SaaS platform. Lead code and design reviews, write infrastructure-as-code, optimize performance and scalability, participate in data governance, mentor junior engineers, evaluate new technologies, automate tests, collaborate cross-functionally, and join on-call rotation to ensure reliable data delivery.

Set up test, preproduction and developer environments on physical servers; act as SQL Server DBA including security auditing; develop Big Data solutions and programs; perform user acceptance and integration testing. Requires experience with DTS/SSIS/SSRS, T-SQL, C#, PowerShell, Hive/Hadoop, and Microsoft SQL Server 2000 certification.

Build and own the core data models and pipelines connecting product usage, accounts, revenue, billing, and customer health. Create trusted metrics, dashboards, and self-serve reporting. Partner with Product, Engineering, and GTM teams to improve data quality, design AI-enabled workflows and agents, and support leadership with accurate visibility into adoption, pipeline, retention, expansion, and revenue.

The Data Engineer will design and maintain data pipelines on Azure, manage ClickHouse for analytics, and ensure healthcare compliance while supporting ML integration.

Design, develop, and maintain batch and streaming data pipelines and ETL for large unstructured datasets. Collaborate with developers, data scientists, and analysts to build data management systems, containerize and deploy services (Docker/Kubernetes), and implement CI/CD, DevOps, and monitoring on Linux/AWS infrastructure for intelligence community missions.

The Data Engineer will construct data infrastructure, develop machine learning workflows, maintain data pipelines, integrate software components, and collaborate across teams to enable data-driven decisions.

Design, build, and maintain scalable relational databases, data warehouses, and integration workflows. Optimize SQL performance, ensure data integrity/security, support reporting/analytics, and collaborate with business stakeholders for timely, compliant reporting and continuity efforts.

Lead end-to-end data integrations with utility customers: scope requirements, map and transform datasets, run and monitor pipelines, triage issues, and productize repeatable tooling to speed implementations.

Leads the design, development, and maintenance of scalable data pipelines, ETL/ELT processes, enterprise data warehouses, and data integrations. Establishes data models, quality standards, governance practices, and documentation while ensuring healthcare data security and interoperability through HL7, FHIR, APIs, and SFTP. Partners with clinical, operational, analytical, and IT stakeholders to deliver reliable data solutions, optimize performance, resolve data issues, and mentor junior staff.

Develop scalable data processing and analytics tools for engineering and business data. Translate stakeholder problems into analytical requirements, build end-to-end ETL and relational data solutions, create user interfaces, perform exploratory analysis, detect trends and anomalies, and communicate actionable insights through effective visualizations and reporting. Collaborate with technical and programmatic teams while following production coding, version-control, and development lifecycle practices.

The description combines recruitment management, event planning, business development consulting, and iOS application development. Responsibilities include developing recruitment strategies, training recruiters, maintaining candidate databases, coordinating events, managing vendors and client relationships, developing sales pipelines, and designing, testing, updating, and maintaining iOS applications.

The description is inconsistent with the title and primarily covers recruitment management, event planning, business development, and iOS application development. Responsibilities include developing recruitment strategies, managing recruiters and candidate databases, coordinating events and vendors, creating business development plans, managing client relationships, and designing, testing, and maintaining iOS applications.