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focuskpi

Data Engineer

Posted 12 Days Ago
In-Office
San Francisco, CA, USA
45-55 Hourly
Mid level
In-Office
San Francisco, CA, USA
45-55 Hourly
Mid level
Build, maintain, and support production-grade data pipelines and platform capabilities. Responsibilities include ingestion, transformation, orchestration, data modeling, testing, monitoring, quality, governance, performance optimization, cost management, CI/CD, and infrastructure automation. The role partners with Analytics, Data Science, Finance, Risk, Marketing, Product, and Engineering teams while supporting Snowflake-based warehouse systems and AI-assisted development initiatives.
The summary above was generated by AI
FocusKPI is looking for a Data Engineer to join our client's growing team 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.
  • 4-5 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 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.

HQ

focuskpi Santa Clara, California, USA Office

1800 Wyatt Dr, Santa Clara, CA, United States, 95054

focuskpi San Francisco, California, USA Office

San Francisco, United States

focuskpi San Jose, California, USA Office

San Jose, United States

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