Data Engineer

Posted 13 Days Ago
San Francisco, CA, USA
In-Office
45-55 Hourly
Mid level
Marketing Tech • Business Intelligence
The Role
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.
Summary Generated by Built In
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.

Skills Required

  • 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
  • Experience building or supporting production data systems
  • Strong programming skills in Python, Java, or another general-purpose language
  • Strong SQL skills
  • Experience building or maintaining ETL/ELT pipelines
  • Experience with 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
  • Experience with Airflow or Cloud Composer
  • Understanding of data modeling, data quality, relational data, query optimization, 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
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The Company
HQ: Santa Clara, CA
31 Employees
Year Founded: 2010

What We Do

FocusKPI brings deep domain experience in business and marketing analytics to enable our clients to unlock growth-driving insights from data. We help our clients develop action-oriented analytics and data science products that are customized to company-specific needs and integrated into their platforms for ongoing use. Our Accelerators, a toolbox of frameworks and models built over 10+ years, fast-track projects by capitalizing on our experience. Capabilities: Predictive Analytics AI / Machine Learning Measurement Text Analysis Key Industries Served: Retail Media B2B & B2C Sales, Marketing, and Merchandising Software & Applications

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