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Job Description
- We are seeking a Data Engineer Team Lead to guide our growing data engineering team in designing, building, and maintaining scalable data infrastructure.
- In this role, you will be both a technical leader and people manager, responsible for mentoring engineers, setting best practices, and ensuring high-quality data systems that support analytics, machine learning, and business decision-making.
Key Responsibilities:
- Technical Leadership
- Design and oversee the development of robust, scalable, and secure data pipelines and architecture.
- Lead the development of data infrastructure using modern tools (e.g., Spark, Airflow, Kafka, dbt).
- Ensure high performance, data quality, and availability across systems.
- Collaborate with data scientists, analysts, and software engineers to support a variety of data initiatives.
- Team Management
- Manage and mentor a team of data engineers, fostering technical growth and career development.
- Set technical direction and establish best practices for data engineering processes and tooling.
- Coordinate team planning, sprint cycles, and project timelines.
- Conduct code reviews, architecture reviews, and provide constructive feedback.
- Cross-functional Collaboration
- Act as a key liaison between engineering, analytics, product, and leadership teams.
- Translate business needs into technical solutions that are efficient, scalable, and aligned with company goals.
Job Requirements
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 5+ years of experience in data engineering, with at least 1–2 years in a leadership role.
- Strong knowledge of SQL and programming languages such as Python, Scala, or Java.
- Experience with cloud platforms (AWS, GCP, or Azure) and modern data stack (e.g., Snowflake, Redshift, BigQuery).
- Hands-on experience with ETL frameworks, orchestration tools (e.g., Airflow), and real-time data streaming (e.g., Kafka).
- Strong understanding of data modeling, data warehousing, and data governance practices.
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