Data Engineer

Wal-Mart; San Francisco (CA); Remote; USD 62,000 - 76,000; Part time

Job summary

FocusKPI is seeking a Data Engineer to join our client's growing team and to help build and improve data systems powering decision-making. You will own data pipelines and production systems, collaborating across Analytics, Data Science, Finance, Risk, Marketing, Product, and Engineering.

Expect to leverage AI-assisted tools while maintaining data quality and security. This 100% remote role spans 4-6 months at 40 hours per week, with a pay range of $45-$55 per hour.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field, or equivalent practical experience.
• 4-5 years of industry experience in software or data engineering, including 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 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.
• 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 with technical/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 from implementation to production support.
• Work with Snowflake, dbt, Airflow, APIs, files, and cloud services to support workload reliability and cost optimization.
• Support warehouse development through schema design, data modeling, testing, and data quality practices.
• Improve ingestion, orchestration, validation, retries, backfills, monitoring, and alerting.
• Use AI-assisted engineering tools to accelerate development while maintaining high standards.
• Own end-to-end data lifecycle management from ingestion to serving layers.
• Ensure data quality, governance, and reliability with testing, observability, lineage, and validation.
• Drive platform optimization and cost efficiency across the data ecosystem.
• Establish engineering best practices: CI/CD, IaC, code reviews, and secure data handling.
• Partner with stakeholders to translate data needs into production-grade solutions.

Skills

Python

SQL

ETL/ELT

Snowflake

dbt

Airflow

Cloud services

CI/CD

Data modeling

Education

Bachelor's degree

Tools

Fivetran

dbt

Airflow

Job description

FocusKPI is looking for a Data Engineerto 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**

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.