Data Engineer

  • Location:

    San Francisco, California 94104 - United States

  • Sector:

    Data Science

  • Job ref:

    1823

  • Contact:

    Lizzie Stanislawski

  • Expiry date:

    2025-10-13

  • Published:

    1 month ago

  • Location: San Francisco, California
  • Type: Contract
  • Job #1823

The Data Engineering team of one of Focus GTS’s clients builds reliable and trusted data sources and products to enable timely and accurate data-driven decision making across the company. They stand at the forefront of data science and business intelligence innovation. By transforming how data is discovered and consumed, laying the groundwork for the future of analytics. They are looking for a Data Engineer to support on a project 

Core offerings:

  • Building and maintaining a foundational data layer, that serves as the single source of truth across
  • Designing and implementing robust data pipelines, guaranteeing data quality and timely data delivery across our organization
  • Pioneering developer tools that inject automation into data science processes, improving efficiency
  • Delivering tailored data products, designed to empower users with self-serve capabilities and ensure accurate answers to their data queries.

What you’ll be doing (ie. job duties):

  • Data modeling: Build and refactor data marts to enhance data discovery and accuracy.
  • Design, architect and maintain a marketing data mart.
  • Introduce automation mechanisms to enforce data best practices and optimal design principles where possible
  • Data pipeline development and optimization: Develop new data pipelines and ETL processes, and enhance the efficiency of existing ones to reduce cost and improve landing times and SLAs.
  • Transition data pipelines to dbt and create features that allow data scientists to utilize the platform.
  • Build scalable systems: Build systems to automate monitoring and alerting for data anomalies
  • Build internal data products aimed at streamlining workflows, minimizing manual interventions and driving operational efficiencies.
  • Collaboration: Collaborate closely with data scientists and other stakeholders to ensure alignment on data needs and deliverables.
  • Maintain clear and comprehensive documentation of processes to facilitate smooth team collaboration and hand-offs.

Skills: What we look for in you (ie. job requirements):

  • Experience with on-chain data analysis, Nansen and Dune Analytics (REQUIRED)
  • Experience working with raw EVM blockchain data (REQUIRED
  • Familiarity with Solana data
  • Data Modeling: Understanding of best practices for data modeling, including star schemas, snowflake schemas, and data normalization techniques.
  • ETL/ELT Processes: Experience in designing, building, and optimizing ETL/ELT pipelines to process large datasets.
  • Apache Airflow: Experience in building, deploying, and optimizing DAGs in Airflow.
  • Python and SQL: Must be adept at scripting in Python, particularly for data manipulation and integration tasks, and have a solid grasp of advanced SQL techniques for querying, transformation, and performance optimization.
  • GitHub: Experience with version control, branching, and collaboration on GitHub.
  • Data Visualization: Knowledge of tools like Superset, Looker or Python visualization libraries (Matplotlib, Seaborn, Plotly…etc)
  • Collaboration and Communication: Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions. Strong documentation skills for pipeline design and data flow diagrams.

Nice to haves:

  • Proficiency in constructing, refining, and managing data pipelines specific to marketing platforms and channels.
  • Experience in the marketing data pipeline and third party tools integration.
  • Familiarity with email management platforms and tools like Iterable and understanding of the data structures that support email targeting.
  • Familiarity with Docker, Kubernetes, and cloud platforms like AWS/GCP
  • Knowledge of fundamental DevOps practices, including unit testing and repository management.
  • Data governance experience preferred
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