About the job Data Engineer
Job Title: Senior Data Engineer or Data Engineer Lead
Reports To: Enterprise Data Group Heads
Employment Type: [Full-time]
Location: [On-site/Hybrid]
Job Summary
We are seeking a highly skilled and motivated Senior or Data Engineer Lead to play a pivotal role in our enterprise data initiatives. This position is responsible for designing, building, and maintaining scalable and efficient data pipelines and data products, ensuring alignment with both enterprise-wide and domain-specific goals. The ideal candidate will combine hands-on expertise in modern data engineering technologies with leadership capabilities to guide junior engineers, define modeling standards, and drive innovation in data architecture.
Key Responsibilities
Data Engineering & Pipeline Development
Design, build, and optimize robust ETL/ELT processes for ingesting data from various sources into Snowflake and Redshift.
Develop high-throughput data pipelines using technologies like Confluent Kafka, SQL, and Python.
Ensure data quality, reliability, and integrity through validation, monitoring, and testing processes.
Troubleshoot data processing issues and lead root cause analysis.
Data Product Design & Modeling
Build and maintain Common Data Products (enterprise-wide canonical models) or Business Data Products (domain-specific models with applied logic and calculations).
Collaborate with stakeholders and architects to translate business needs into scalable, reusable data models.
Define and enforce modeling standards, naming conventions, documentation practices, and test strategies using DBT.
Leadership & Collaboration
Mentor and guide junior engineers through code reviews, technical coaching, and design oversight.
Drive continuous improvement in data engineering practices, tool adoption, and process optimization.
Deliver technical and executive updates to stakeholders and leadership.
Participate in Proof of Concept (PoC) initiatives to evaluate and recommend new tools or frameworks.
Qualifications and Skills
Required:
Bachelors degree in Computer Science, Information Technology, Data Science, or a related field.
7+ years of experience in data engineering, data architecture, or related roles.
Advanced proficiency in SQL and Python.
Strong experience with Snowflake, Redshift, and DBT for ELT modeling and data warehousing.
Hands-on experience with streaming platforms such as Confluent Kafka.
Proven ability to design and support data warehouses, data products, and data hubs.
Strong analytical skills and the ability to communicate complex data solutions clearly.
Preferred:
Familiarity with data mesh principles, modular data product design, or enterprise data governance.
Knowledge of data quality, data architecture, and master data management concepts.
Experience with CI/CD pipelines and modern data orchestration tools.
Familiarity with cloud-based data platforms and optimization of ELT data flows.
Experience working with Snowflake, DBT, and version control systems like Git.