Data Engineer
100% remote
6-month W2 contract to hire
Job Overview:
As a Data Engineer, you will be responsible for designing, building, and maintaining efficient and scalable data pipelines and data-centric solutions. You will collaborate closely with cross-functional IT teams, data analysts, data scientists, and other stakeholders to ensure the availability, reliability, and accessibility of data to support various business needs.
Key Responsibilities:
Data Pipeline Development: Design, develop, and optimize data pipelines for data ingestion, transformation, and storage.
ETL/ELT Processes: Build and manage Extract, Transform, Load (ETL) processes to ensure timely, clean, and accurate data for analytics and reporting.
Data Integration: Integrate data from various internal and external data sources into the organization's data platform.
Database Management: Work with relational databases (e.g., SQL Server) and potentially non-relational databases to store, retrieve, and manage large datasets.
Data Governance: Implement and enforce data quality, governance, and security policies to ensure compliance with regulatory and company standards.
Optimization: Optimize data workflows, query performance, and storage solutions for efficiency and cost-effectiveness.
Automation: Automate repetitive data processes and workflows to improve efficiency and reduce errors.
Monitoring & Troubleshooting: Implement monitoring, alerting, and troubleshooting processes for data systems to ensure high availability and performance.
Experience:
Must have 3+ years of experience in data engineering, software development, or related field.
Technical Skills:
Strong SQL skills (complex queries, performance tuning, relational modeling).
Experience developing and optimizing data solutions in Snowflake.
Hands-on data development experience with dbt (dbt Core and/or dbt Cloud), including modular modeling, testing, and documentation.
Experience with relational databases such as SQL Server (or similar enterprise RDBMS).
Proficiency with at least one programming/scripting language used for data engineering (e.g., T-SQL, Python, or similar).
Solid understanding of data warehousing concepts (dimensional modeling, staging/curation layers, incremental processing).
Familiarity with Git and collaborative development workflows (branching, pull requests, code reviews).
Understanding of SDLC and project delivery practices (requirements, design, build, test, deploy, support).
Soft Skills:
Excellent problem-solving and analytical skills.
Strong communication skills with the ability to work in cross-functional teams.
Ability to manage multiple tasks in a fast-paced environment.
Strong attention to detail and commitment to delivering high-quality work.