Lead Data Engineer - Technology Data Product

Location:

4910 Tiedeman Road, Brooklyn Ohio

Job Summary We are seeking a Lead Data Engineer to support the design, implementation, maintenance, and lifecycle of enterprise data products starting with our Dev Ops Data Product transforming technology, operational, and business data into trusted, governed, and reusable  this hands-on technical leadership role, you will partner with Data Product Owners, data modelers, data architects, platform engineers, technology teams, and business stakeholders to develop scalable data pipelines, reusable data models, cloud-native services, and deployment automation on Google Cloud Platform.

This is a strong fit for someone who enjoys solving complex data and platform problems, improving data quality and reliability, reducing friction in the data delivery and pipeline lifecycle, and building standardized solutions that encourage broad adoption. The role offers the opportunity to influence data engineering standards, strengthen platform capabilities, and help shape a delivery ecosystem built for speed, quality, governance, and resilience.

Essential Functions Data Pipeline Engineering:
Design, build, and support production batch and incremental pipelines using Python, SQL, and Cloud Composer to collect and process data and telemetry from enterprise tools and source systems.

Big Query Engineering & Optimization:
Implement and maintain Big Query datasets, tables, views, and transformation workloads. Optimize partitioning, clustering, query performance, access, storage, and compute costs.

Data Transformation & Testing:
Write and deploy automated transformation workflows and data quality checks using Dataform.

CI/CD & Infrastructure as Code:
Create and maintain repeatable Terraform configurations and Git Lab CI/CD pipelines to automate testing, credential handling, and environment deployments across development, test, and production.

System Integration & Security:
Build secure integrations with enterprise APIs and source systems using appropriate authentication and credential management, incorporating retry, error handling, and rate-limiting patterns.

Data Quality & Reliability:
Configure pipeline monitoring, alerting, schema validation, and reconciliation jobs.

Data Product Delivery:
Partner with the Data Product Owner, data modelers, architects, and platform teams to translate product requirements, metric definitions, data-quality expectations, and governance requirements into reliable technical solutions.

Documentation & Governance:
Maintain technical documentation, lineage, data contracts, implementation guides, and evidence needed to support governance and audit requirements.

Technical Mentorship & Standards:
Conduct code reviews, establish reusable coding templates, and mentor team engineers on best practices for data engineering and version control.

Required Technical SkillsSQL & Big Query:
Advanced SQL proficiency with hands-on Big Query experience managing datasets, partitioning, clustering, views, schema updates, access controls, and query optimization.

Data Pipeline & Orchestration:
Proven experience designing and running production ELT/ETL pipelines, state management, incremental loading, and workflow scheduling with Cloud Composer or Apache Airflow.

Programming & Scripting:
Strong hands-on programming skills in Python and Bash shell scripting for container and pipeline workflows.

API Ingestion:
Practical experience extracting data from enterprise REST or GraphQL APIs, handling pagination, rate limits, OAuth flows, and integration with secret management systems.

Dataform / SQL Transformation:
Hands-on experience developing modular data transformations, dependencies, and automated test assertions using Dataform or comparable SQL-based frameworks.

Terraform &…