Data Engineer
FocusKPI, Inc., New York, NY, United States
Data Engineer
Work Location:
100% remote and ideally able to work New York EST hours
Duration:
5 months / 40 hrs per week
Pay Range:
$45 - $55/hr
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.
Qualifications:
Bachelor’s degree in a Computer Science or related field; STEM majors; MS degree preferred.
5+ years
of industry experience.
Experience with 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 stakeholders from product, marketing, finance, and other business functions.
Experience handling large‑scale data efficiently.
Strong analytical and problem‑solving skills.
Experience in Financial Services or FinTech preferred.
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Work Location:
100% remote and ideally able to work New York EST hours
Duration:
5 months / 40 hrs per week
Pay Range:
$45 - $55/hr
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.
Qualifications:
Bachelor’s degree in a Computer Science or related field; STEM majors; MS degree preferred.
5+ years
of industry experience.
Experience with 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 stakeholders from product, marketing, finance, and other business functions.
Experience handling large‑scale data efficiently.
Strong analytical and problem‑solving skills.
Experience in Financial Services or FinTech preferred.
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