SQL Engineer

About the Role

Key Responsibilities

Data Modeling & Architecture

Design, optimize, and maintain dimensional models (star/snowflake) supporting manufacturing, IoT telemetry, device connectivity, quality, service, and regulatory use cases.
Build scalable warehouse structures in Amazon Redshift, including efficient distribution keys, sort keys, compression encodings, and metadata strategies.
Model complex entities such as device fleets, IoT events, sensor readings, battery health, shift-level utilization, production batches, quality defects, and MES/WMS/ERP entities.

SQL Engineering & ELT Development

Develop high-performance SQL, stored procedures, and ELT jobs that integrate data from:
ERP (Epicor, NetSuite, SAP)
MES/WMS systems
IoT device platforms and telemetry feeds
Quality, service, and regulatory systems
Optimize complex SQL workloads using query plan analysis, statistics, compression, and cluster tuning.
Implement SCD Type 1/2 structures, bridge tables, audit trails, and CDC-style processes.
Build reusable SQL patterns for fleet-level telemetry, battery analytics, connectivity uptime, and traceability.

Production Reliability & Data Governance

Own end-to-end Redshift performance, cost, and reliability for mission-critical tables and processes.
Implement durable auditability and row-level lineage for medical device data (supporting FDA and HIPAA standards).
Participate in on-call/incident response for critical production data issues.

Cross-Functional Collaboration

Work closely with manufacturing engineering, operations, quality, field service, regulatory, and product teams.
Translate business requirements and ambiguous real-world device behavior into precise, validated SQL logic.
Provide technical leadership on data modeling, performance tuning, and SQL coding standards.

Required Skills & Experience

5–10+ years of production-grade SQL development, including advanced windowing, CTEs, dynamic SQL, query plan interpretation, and stored procedures.
Expert-level experience with Amazon Redshift (or deep experience on equivalent MPP systems like Snowflake/BigQuery + strong willingness to operate in Redshift).
Mastery of dimensional modeling (Kimball), including SCDs, conformed dimensions, bridge tables, and history management.
Experience working with manufacturing, IoT, or medical device data—telemetry, event streams, MES/ERP/WMS integration, batch/lot traceability, or uptime analytics.
Strong ability to convert complex business rules into precise, scalable SQL logic.
Solid understanding of AWS ecosystem: Redshift, Step Functions, Lambda, Glue, S3, IAM.
Scripting proficiency in Python for orchestration, validation, AWS automation, and Glue/Airflow-like pipelines.
Familiarity with quality/regulatory expectations in healthcare or medical devices (e.g., audit trails, data retention, validation documentation).

Highly Valued (Nice-to-Have)

Experience with connected medical devices, IoT fleet analytics, or device telemetry pipelines.
Background in regulated environments (FDA, ISO 13485, 21 CFR Part 11).
Exposure to AWS Glue ETL, Step Functions workflows, and Lambda-driven orchestration.
Knowledge of dbt or SQL-based modeling frameworks.
Experience with data lineage or cataloging tools (e.g., Alation, Collibra, Monte Carlo).

You’ll Thrive Here If You…

Treat performance, reliability, and data integrity as non-negotiable.
Enjoy reverse-engineering device behavior and manufacturing processes and expressing them in elegant SQL models.
Think like an engineer and like a business analyst—translating real operational workflows into accurate data structures.
Are passionate about making data usable, trusted, traceable, and production-ready.
Communicate clearly with technical and non-technical stakeholders alike.