Were looking for a Senior Data Engineer to help scale our data platform and deliver reliable, high-quality data services to both internal teams and external customers. If you thrive on solving complex data challenges, collaborating with diverse stakeholders, and building scalable systems that last, wed love to meet you.
What Youll Own:
Design and implement scalable ETL pipelines using Apache Spark and related technologies.
Build robust data services to support multiple internal teams, including product and analytics.
Architect end-to-end data solutions and translate them into actionable engineering plans.
Maintain clean, reliable data interfaces for microservices and systems requiring accurate, timely data.
Collaborate closely with product teams to understand data needs and co-create solutions.
Ensure observability, data quality, and pipeline reliability through monitoring and automated validation.
Participate in code reviews, architecture discussions, and mentor less experienced engineers.
What Youll Own:
Design and implement scalable ETL pipelines using Apache Spark and related technologies.
Build robust data services to support multiple internal teams, including product and analytics.
Architect end-to-end data solutions and translate them into actionable engineering plans.
Maintain clean, reliable data interfaces for microservices and systems requiring accurate, timely data.
Collaborate closely with product teams to understand data needs and co-create solutions.
Ensure observability, data quality, and pipeline reliability through monitoring and automated validation.
Participate in code reviews, architecture discussions, and mentor less experienced engineers.
Requirements:
6+ years of experience building and maintaining production-grade ETL pipelines.
Hands-on experience with orchestration tools such as Databricks, Airflow, dbt, or similar.
Proven ability to design systems that support diverse data consumers with varying SLAs.
Deep understanding of data modeling, distributed systems, and cloud infrastructure.
Strong background in Apache Spark (PySpark or Scala).
Familiarity with microservices architectures and clean API/data contracts.
Excellent communication and collaboration skills youre proactive, approachable, and solution-oriented.
Ability to think in systems: conceptualize high-level architecture and break it into components.
Nice to Have:
Knowledge of data governance, lineage, and observability best practices.
Experience with real-time streaming technologies (e.g., Kafka, Flink).
Exposure to DevOps practices for data systems, including CI/CD, monitoring, and infrastructure-as-code.
Previous experience developing customer-facing data products or analytics tools.
6+ years of experience building and maintaining production-grade ETL pipelines.
Hands-on experience with orchestration tools such as Databricks, Airflow, dbt, or similar.
Proven ability to design systems that support diverse data consumers with varying SLAs.
Deep understanding of data modeling, distributed systems, and cloud infrastructure.
Strong background in Apache Spark (PySpark or Scala).
Familiarity with microservices architectures and clean API/data contracts.
Excellent communication and collaboration skills youre proactive, approachable, and solution-oriented.
Ability to think in systems: conceptualize high-level architecture and break it into components.
Nice to Have:
Knowledge of data governance, lineage, and observability best practices.
Experience with real-time streaming technologies (e.g., Kafka, Flink).
Exposure to DevOps practices for data systems, including CI/CD, monitoring, and infrastructure-as-code.
Previous experience developing customer-facing data products or analytics tools.
This position is open to all candidates.
