Dataops Engineer Jobs in California (NOW HIRING)

We are looking for a Senior/Lead Data Engineer to join a major insurance programme and lead the design, development, and optimisation of enterprise data warehouse and pipeline solutions.

This is a deeply hands-on role for someone who is genuinely strong in Python, SQL, and Snowflake, and who can operate at senior level across data engineering design, production pipeline ownership, data quality, performance tuning, and technical leadership. This is not just an execution role. We are looking for someone who can set direction, raise engineering standards, mentor others, and solve complex data platform problems in a live enterprise environment.

Data Platform Engineering

• Lead the design, development, and optimisation of enterprise-grade data pipelines for warehouse, analytics, and downstream reporting use cases
• Build and enhance Python-based frameworks for ingestion, transformation, validation, orchestration, and automation
• Design and optimise Snowflake-based data structures, semantic layers, and reporting models for scalability, reliability, and cost efficiency
• Write and review advanced SQL for transformation, reconciliation, performance tuning, troubleshooting, and large-scale data analysis

Pipeline Ownership & Data Quality

• Establish robust ETL/ELT standards, reusable patterns, and engineering best practices across structured and semi-structured data sources
• Own data quality, validation, reconciliation, observability, and root cause analysis for complex data issues
• Drive reliability, monitoring, alerting, deployment, and production support for critical data pipelines
• Support incident response and resolution for high-impact data engineering issues

Technical Leadership

• Mentor mid-level and junior engineers through code reviews, design reviews, and knowledge sharing
• Lead technical discussions and contribute to design decisions across the data platform
• Work closely with business stakeholders, analysts, architects, and engineering teams to translate requirements into robust technical solutions
• Champion coding standards, testing, CI/CD, documentation, and disciplined production practices across the team

Must-Have

• 10+ years of experience in data engineering, analytics engineering, or related data platform roles
• Expert-level hands-on Python experience; weak Python is a disqualifier
• Advanced SQL skills, including complex transformations, window functions, query optimisation, and performance tuning at scale
• Strong experience designing, building, and maintaining large-scale production data pipelines
• Deep practical knowledge of Snowflake, including performance tuning, warehouse sizing, clustering, and cost optimisation
• Strong understanding of ETL/ELT patterns, batch processing, and incremental / CDC approaches
• Experience with structured and semi-structured data such as JSON, Parquet, Avro
• Strong ownership mindset around data quality, validation, reconciliation, and observability
• Ability to produce clean, maintainable, well-tested, production-ready code
• Strong analytical thinking, problem solving, and system design capability
• Ability to work Pacific Time
• Strong communication and stakeholder management skills
• Ability to mentor engineers and lead technical/code/design discussions
• Comfortable with a live coding assessment in Python and SQL

Preferred

• DBT
• Azure services such as Data Factory, ADLS, Functions, DevOps
• Experience with orchestration tools such as Airflow, Prefect, Dagster, or similar
• Experience with Salesforce data models or Salesforce integration patterns
• Experience in insurance, financial services, or other regulated environments
• Exposure to data governance, lineage, metadata, CI/CD for data, Terraform, or broader DataOps practices

• You are not just a pipeline builder, you can shape engineering patterns and raise the bar for the team
• You combine deep Snowflake + Python + SQL capability with real production ownership
• You can solve data trust, quality, and reconciliation problems, not just move data between systems
• You are senior enough to lead technically, while still staying genuinely hands-on