Senior Data Engineer
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Summary
Designs and leads enterprise-scale data pipelines, warehouses, and multi-cloud data platforms (AWS, Azure, GCP) powering analytics and AI-driven decisions. Day to day: architecting ETL/ELT with Airflow, dbt and Snowflake, automating with Terraform/CI-CD, setting data governance standards, and mentoring engineers.
The Senior Data Engineer designs and leads enterprise-scale data pipelines, warehouses, and multi-cloud data platforms that support trusted analytics and AI-driven decision-making. This role sets technical direction, establishes engineering standards, and mentors teams while ensuring data quality, security, governance, scalability, and performance.
Responsibilities
- Architect and optimize end-to-end ETL/ELT pipelines and reusable data integration frameworks
- Define enterprise data modeling standards across star, snowflake, and data vault architectures
- Lead deployment and performance optimization of data solutions across AWS, Azure, and GCP
- Establish data quality, governance, monitoring, security, and compliance frameworks
- Drive automation, process improvements, and engineering best practices across teams
- Deliver trusted, documented, and accessible data for analytics, reporting, and data science
- Lead technical decisions, solution design, delivery planning, and execution across multiple workstreams
- Mentor junior and mid-level engineers and guide cross-functional teams
Required Experience & Skills
- 8-12 years for Senior building enterprise-scale data platforms
- Proven experience designing end-to-end data architectures and leading cross-functional teams
- Advanced SQL, enterprise data modeling, and performance optimization
- Strong Python for reusable pipeline frameworks and automation
- Deep expertise in ETL/ELT architecture and orchestration, including Airflow and dbt
- Strong hands-on experience with Snowflake and multi-cloud architectures
- Experience with Terraform, infrastructure as code, CI/CD, and automated deployments
- Expertise in data quality frameworks, SLAs, observability, metadata, lineage, access controls, and compliance
- Strong technical leadership, mentoring, stakeholder communication, and AI fluency
Preferred Experience (Nice to have)
- Experience leading enterprise-scale, multi-cloud data programs
- Exposure to analytics, BI, and AI/ML data platform use cases
- Hands-on experience with BigQuery, Tableau, or Power BI
- Relevant certifications in Snowflake, AWS, Azure, or GCP