Lead Data Engineer to design and implement scalable data pipelines and analytics-ready datasets, define data models and standards, guide engineering work, collaborate with stakeholders, and contribute to data platform architecture, quality, and governance.
We are looking for a Lead Data Engineer to drive the design and implementation of scalable data solutions, pipelines, and analytics-ready datasets.
What You’ll Do
- Lead design and implementation of data pipelines, transformations, and curated datasets
- Translate business requirements into structured data solutions and models
- Guide and execute development of reusable, analytics-ready data assets
- Ensure consistency in how key data elements are defined and used across systems
- Collaborate with stakeholders to define and refine data requirements and logic
- Review and guide engineering work to ensure quality, performance, and scalability
- Establish best practices for data engineering, transformation, and data quality
- Support integration of data across multiple domains and systems
- Contribute to architecture decisions across data platforms and tooling
- Mentor and support other engineers on the team
What You Bring
Must-Haves
- 5+ years of experience in data engineering, analytics engineering, or related fields
- Strong SQL expertise and experience designing complex data transformations
- Hands-on experience with modern data platforms (e.g., GCP BigQuery, Databricks, Snowflake)
- Data platforms experience. ELT or ETL, orchestration such as Airflow or dbt, Spark, data warehouses and lakehouses such as Snowflake, BigQuery, or Databricks, streaming such as Kafka or Kinesis, metadata and data quality
- Proficiency in Python
- Strong understanding of data modeling concepts and data structuring for analytics
- Experience working with stakeholders to define requirements and deliver data solutions
- Ability to balance hands-on delivery with technical guidance
Nice-to-Haves
- Familiarity with data governance, lineage, or metadata management concepts
- Experience working with cross-domain data (e.g., customer, product, transactions)
- Exposure to financial services or other data-intensive industries
- Experience supporting migration or evolution of data platforms (e.g., toward Databricks)
- Experience with orchestration tools (e.g., Airflow, Cloud Composer)
- Exposure to data modeling concepts (e.g., dimensional models, data marts, reusable datasets)
What’s in It for You
- Impact at scale. Help shape enterprise AI, software, and data programs across industries.
- Growth and mastery. Work with a seasoned team from leading consulting and technology backgrounds.
- Build real products. Work on production ready assets with autonomy over key technical decisions.
About Us
Established in 2011, Trinetix is a dynamic tech service provider supporting enterprise clients around the world.
Headquartered in Nashville, Tennessee, we have a global team of over 1,000 professionals and delivery centers across Europe, the United States, and Argentina. We partner with leading global brands, delivering innovative digital solutions across Fintech, Professional Services, Logistics, Healthcare, and Agriculture.
Our operations are driven by a strong business vision, a people-first culture, and a commitment to responsible growth. We actively give back to the community through various CSR activities and adhere to international principles for sustainable development and business ethics.
To learn more about how we collect, process, and store your personal data, please review our Privacy Notice: https://www.trinetix.com/corporate-policies/privacy-notice
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