Sr. Data Engineer
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Summary
Senior Data Engineer who designs, builds, and optimizes automated ETL/ELT data pipelines, data models, and data marts on cloud data platforms (Databricks/Snowflake, preferably Azure). Day to day includes large-scale data migration, pipeline monitoring and troubleshooting, governance compliance, documentation, and mentoring junior engineers.
Job Description
- Design, build, and optimize automated data pipelines, ETL/ELT processes, and data models to ingest, process, and store large volumes of data within cloud-based platforms.
- Support large-scale data migration initiatives, ensuring data accuracy, performance efficiency, and minimal business disruption.
- Develop and maintain ETL/ELT workflows to ingest, transform, and load data from multiple internal and external sources with a focus on scalability and reliability.
- Partner with business, analytics, and product teams to translate data requirements into effective technical solutions that support strategic initiatives.
- Design and deliver data marts and customized data extractions aligned with business and reporting needs.
- Ensure compliance with enterprise data governance, security, and regulatory standards. Monitor data pipeline health and performance, troubleshoot data incidents, and implement preventive and corrective measures.
- Document data workflows, schemas, technical specifications, and operational runbooks to support operational stability and knowledge transfer.
- Collaborate closely with product owners, data architects, and data scientists to maintain a reliable and efficient data infrastructure.
- Drive continuous improvement of data engineering practices, tools, and automation frameworks.
- Provide technical guidance and mentorship to junior engineers through code reviews, best-practice sharing, and troubleshooting support.
- Manage and deliver multiple data engineering initiatives concurrently while meeting quality, scope, and timeline expectations.
Requirements
Experience
- At least 8 years of total Data Engineering experience, with strong exposure to large-scale data pipelines, ETL/ELT development, and enterprise or cloud-based data platforms.
- Proven experience designing, building, and optimizing scalable data solutions in modern data environments.
Knowledge
- Python – At least 4 out of 5 proficiency level, with strong hands-on experience in data transformation, automation, and pipeline development.
- SQL – At least 3 out of 5 proficiency level, with demonstrated capability in complex queries, data modeling, and performance tuning.
- Experience working with modern data cloud platforms, such as Databricks and/or Snowflake.
- Experience with cloud services, preferably Microsoft Azure (e.g., Azure Data Factory, Azure Synapse, Azure Storage, etc.).
- Platform and Cloud Exposure - Currently working with or has recent hands‑on experience in enterprise-grade cloud data ecosystems. With a strong understanding of cloud-native data architecture and best practices.
Soft Skills
- Strong verbal and written communication skills
- Demonstrated leadership and technical influence
- Strong analytical, critical thinking, and problem-solving abilities
- Process orientation with the ability to enforce standards and best practices
- Strong organizational, multitasking, and time-management skills
- Stakeholder and cross-functional collaboration skills