Senior Data Engineer

Summary

Join Flex, a rapidly growing finance super app company, as a Senior Data Engineer. You will play a crucial role in building data systems that transform raw business data into actionable insights. This fully remote position offers the opportunity to work with a talented team, influence technical design, and make a significant long-term impact. You will collaborate with stakeholders, architect data pipelines, identify data gaps, and implement automation for data processing. The ideal candidate possesses advanced experience in data pipeline development, relational databases, and data analysis, along with experience with various tools and technologies.

Requirements

• Advanced experience building, optimizing, and maintaining data pipelines and data sets
• Demonstrated strong experience working with relational databases, query authoring as well as working familiarity with a variety of databases and data warehouses like Postgres, Snowflake, or similar
• Ability to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with unstructured datasets
• Experience with data pipeline and workflow management tools like Airflow
• Familiarity with cloud based providers like Google Cloud, AWS, or Azure and related data services like BigQuery, Dataproc, Dataflow, etc
• Experience with programming languages like Python, C#, Java, Scala, etc
• Knowledge of Retool or Tableau
• Exposure to stream-processing systems: Beam, Spark Streaming, Kafka Streams, etc
• Four or more years of relevant industry experience with a track record of shipping high-quality products and features at scale

Responsibilities

• Collaborate with stakeholders across the company to build aggregated and curated datasets, dashboards, and APIs to support getting the right data to the right people at the right time
• Architect, implement, and manage batch and real-time data pipelines, models, and ETLs to surface new internal and third-party data sources for easy analysis
• Identify gaps and invent processes, automated scripts, and tools to efficiently carry out data processing tasks in a scalable fashion
• Utilize logging, observability, and notifications for workflows
• Contribute to advancing goals around data governance policy creation/enforcement, business metadata cataloging, and access control
• Own the process and automation for data intake, QA, and data delivery
• Be a catalyst for driving best-in-class technology frameworks and tooling while staying engaged with the latest technology trends