Data Engineer

• 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

• 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

FocusKPI Inc. is an analytics consulting company servicing Fortune 500 clients in the IT industry.

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