Data Engineer

FocusKPI Inc.

United States

Remote

USD 62,000 - 76,000

Part time

14 days+

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Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field.
  • 4-5 years of industry experience in software or data engineering, including experience building or supporting production data systems.
  • Strong programming skills in Python, Java, or another general-purpose language, plus strong SQL skills.
  • Experience building or maintaining ETL/ELT pipelines and working with tools such as dbt, Fivetran, or similar.
  • Hands-on experience building production pipelines for data ingestion into a data warehouse.
  • Experience with cloud data warehouses like Snowflake, BigQuery, or Redshift and orchestration tools such as Airflow.
  • Understanding of data modeling, data quality, relational data, and query/performance optimization.
  • Strong software engineering fundamentals including version control, testing, code reviews, and CI/CD.
  • Ability to troubleshoot production systems and communicate with technical and business partners.
  • Experience in Financial Services or FinTech preferred.

Responsibilities

  • Build, maintain, and improve data pipelines across the client’s data platform.
  • Own data engineering projects through implementation, testing, deployment, monitoring, troubleshooting, and ongoing support.
  • Work with Snowflake, dbt, Airflow/Cloud Composer, APIs, files, and cloud services to support production workloads and optimize them for reliability, performance, scalability, and cost.
  • Support warehouse development through schema design, data modeling, testing, documentation, data quality practices, and query optimization.
  • Improve ingestion, orchestration, validation, retries, backfills, monitoring, and alerting while reducing recurring operational work.
  • Use AI-assisted engineering tools to accelerate development, debugging, documentation, and analysis while maintaining high standards for accuracy, security, review, and engineering judgment.
  • 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.
  • Establish engineering best practices — CI/CD, Infrastructure as Code, reviews, documentation, and secure data handling.
  • Partner cross-functionally with technical and business stakeholders to translate data needs into reliable, production-grade solutions

Skills

Python
SQL
Java
Data pipelines

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field

Tools

dbt
Fivetran
Snowflake
BigQuery
Redshift
Airflow

Job description

FocusKPI is looking for a Data Engineer to join our client’s growingteam and to help build and improve the data systems that power decision-making. You’ll develop reliable pipelines and platform capabilities while growing your ownership of production data systems and the business outcomes they support.

Data is central to how the client builds products, manages risk, understands our members, and makes decisions. In this role, you’ll work alongside experienced Data Engineers and partners across Analytics, Data Science, Finance, Risk, Marketing, Product, and Engineering. You’ll own well-defined data engineering projects from implementation through production support and help make our platform more reliable, scalable, and efficient. You’ll also have opportunities to apply AI-assisted development tools and support emerging AI initiatives as they evolve how they build and use data.

Work Location: 100% remote
Duration: 4-6 months/ 40 hrs per week
Pay Range: $45 - $55/hr

**No C2C resumes are considered**

Responsibilities
  • Build, maintain, and improve reliable data pipelines that ingest, transform, and deliver data across the client’s data platform.
  • Own data engineering projects and pipelines through implementation, testing, deployment, monitoring, troubleshooting, and ongoing support.
  • Work with Snowflake, dbt, Airflow/Cloud Composer, APIs, files, and cloud services to support production workloads and optimize them for reliability, performance, scalability, and cost.
  • Support warehouse development through thoughtful schema design, data modeling, testing, documentation, data quality practices, and query optimization.
  • Improve ingestion, orchestration, validation, retries, backfills, monitoring, and alerting while helping reduce recurring operational work.
  • Use AI-assisted engineering tools thoughtfully to accelerate development, debugging, documentation, and analysis while maintaining strong standards for accuracy, security, review, and engineering judgment.
  • 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 Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
  • 4-5years of industryexperience in software or data engineering, including experience building or supporting production data systems.
  • Strong programming skills in Python, Java, or another general-purpose language, plus strong SQL skills.
  • Experience building or maintaining ETL/ELT pipelines and working with technologies such as dbt, Fivetran, or similar tools.
  • Hands-on experience building production pipelines for file ingestion into a data warehouse.
  • Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift and orchestration tools such as Airflow or Cloud Composer/Good experience with Airflow.
  • Understanding of data modeling, data quality, relational data, and query and performance optimization.
  • Strong software engineering fundamentals , including version control, testing, code reviews, and CI/CD.
  • Ability to troubleshoot production systems methodically and communicate effectively with technical and business partners.
  • Experience in Financial Services or FinTech preferred

**No C2C resumes are considered**

Thank you!

FocusKPI Hiring Team

Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California, with an East Coast office in Boston, Massachusetts.

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