Role overview

Senior Data Engineer (AWS, Python & SQL)

Requirements and responsibilities

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Responsibilities

  • Design, build, and maintain scalable data pipelines for analytics, ecommerce, logistics, and marketing.
  • Improve and maintain the company's data infrastructure and tooling, including Redshift/Snowflake, Airflow, and Fivetran.
  • Architect data processing systems capable of handling complex data flows and large-scale datasets.
  • Develop reliable, efficient, and cost-effective data solutions in an AWS environment.
  • Ensure high standards of data quality through automation and best engineering practices.
  • Optimize platform performance, resiliency, scalability, and operational costs.
  • Collaborate closely with software engineers, analysts, and business stakeholders.
  • Mentor engineers and analysts on data engineering best practices.
  • Participate in architecture discussions and technical decision-making.

Must haves

  • 4+ years of experience as a Data Engineer working with modern data technologies.
  • Strong proficiency in Python and SQL.
  • Experience processing large-scale datasets.
  • Hands-on experience with Apache Spark and Apache Airflow.
  • Experience designing and architecting data processing systems in AWS.
  • Experience with Redshift and/or Snowflake.
  • Knowledge of Fivetran or similar data ingestion tools.
  • Strong understanding of data quality, automation, and data engineering best practices.
  • Excellent communication and interpersonal skills.

Nice to haves

  • Experience with streaming technologies such as Kafka or AWS Kinesis Firehose.
  • Knowledge of Docker and/or Kubernetes.
  • Familiarity with Ruby or R.
  • Experience building or migrating a Data Warehouse.
  • Experience leading projects or mentoring technical teams.
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Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Docker, KubernetesPrimary skills
Location25 accepted countriesEligibility

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