Sr. Data Engineer

Overview

Company that is revitalizing the manufacturing industry via technology, is looking for a Sr. Data Engineer to work across hybrid environments—on-prem and cloud—to automate data movement, validate data quality, and enable analytical teams to derive insights from trusted, well-organized datasets.

To note: this is a hybrid, three days a week, in office role to Downtown Los Angeles, and the candidate must be a US Citizen or Permanent Resident (Green Card Holder) not needing future sponsorship.

• Co-design data interfaces and pipelines in close collaboration with software engineers and technical leads, ensuring alignment with application domain models and product roadmaps.
• Model curated data within the lake into data warehouse structures (e.g., star schemas, wide tables, semantic layers) optimized for business intelligence (BI), ad-hoc analytics, and key performance indicator (KPI) reporting.
• Establish robust data observability and quality checks to ensure reliability and consistency.
• Operate the platform reliably by orchestrating jobs, monitoring pipelines, and continuously tuning cost and performance.
• Utilize modern data technologies to operationalize and expand the enterprise Data Lake.
• Implement efficient ingestion strategies, integrating diverse data sources, and ensuring data is structured for accessibility and analysis

• Bachelor’s degree (BA/BS) in Computer Science, Data Science, Mathematics, Analytics, or a related quantitative field (or equivalent experience).
• 5-8+ years of proven experience building production-grade data systems with a strong understanding of cloud-based data lake architectures and data warehouses.
• Demonstrated expertise in designing and operating data pipelines, including schema evolution, backfills, and performance tuning.
• Hands-on proficiency with Python and SQL, including experience with distributed processing frameworks (e.g., Apache Spark) and CI/CD for data workflows.
• Proven ability to design and implement ETL/ELT workflows and data modeling techniques (e.g., star schemas, wide tables, semantic models).
• Proficiency with cloud data platforms and services such as AWS, Databricks, and Snowflake, with a focus on scalability and reliability.
• Familiarity with open table formats (e.g., Iceberg, Delta, Hudi) and business intelligence data modeling.
• Experience or strong interest in enabling AI/ML use cases.

Do you want to help design data pipelines, warehouse, and lakes from scratch for an industry leading organization? Send your resume, along with your application, and let's chat!