Data Engineer

FocusKPI Inc.New York, NY
$45 - $55Remote

About The Position

FocusKPI is looking for a Data Engineer to join our client's growing team and spearhead analyses, providing meaningful insights into their users and product. This is a 5-month contract position with 40 hours per week, fully remote, and ideally requires the candidate to work New York EST hours. The pay range is $45 - $55/hr. No C2C resumes are considered.

Requirements

  • Bachelor’s degree in the Computer field, which requires logical, creative thinking, STEM majors, MS degree preferred
  • 5+ years of industry experience are required
  • Team's Tech Stack: Spark, Scala, Python, DBT, Airflow, Kafka, AWS EMR, Hive, Redshift, Docker, Lambda, SNS, SQS, S3, Looker, DynamoDB, GitHub Actions, Terraform
  • Experience with data models
  • Experience with CI/CD
  • Experience collaborating with and understanding the needs of stakeholders from a variety of business functions, including product, marketing, finance, and so on
  • Experience in handling large-scale data with efficiency
  • Strong analytical and problem-solving skills

Nice To Haves

  • Experience in Financial Services or FinTech preferred

Responsibilities

  • Architect and scale modern data platforms on AWS — Design and build robust, scalable Spark-based ETL/ELT pipelines and data workflows supporting batch and real-time use cases.
  • Own end-to-end data lifecycle management — From ingestion and transformation to modeling, orchestration, and serving layers.
  • Ensure data quality, governance, and reliability — Implement testing frameworks, observability, monitoring, lineage, and data validation practices.
  • Drive platform optimization and cost efficiency — Continuously improve performance, scalability, and cloud cost management across the data ecosystem.
  • Establish engineering best practices — CI/CD, Infrastructure as Code, code reviews, documentation standards, and secure data handling.
  • Partner cross-functionally with technical and business stakeholders to translate data needs into reliable, production-grade solutions
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