We are looking for an experienced Data Engineer Lead to design, build, and optimize scalable data pipelines and architectures. The ideal candidate will lead a team of data engineers, drive best practices, and ensure high-quality, reliable data solutions that support business analytics and decision-making.
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Lead the design and development of scalable, high-performance data pipelines and ETL/ELT processes
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Architect and manage data platforms, data lakes, and data warehouses
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Collaborate with cross-functional teams including Data Science, Analytics, and Product
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Ensure data quality, integrity, security, and governance standards are maintained
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Mentor and guide junior data engineers, conducting code reviews and enforcing best practices
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Optimize data workflows for performance, scalability, and cost efficiency
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Manage cloud-based data infrastructure (AWS, Azure, or GCP)
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Troubleshoot complex data issues and provide timely resolutions
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Stay updated with emerging technologies and recommend improvements
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Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
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8+ years of experience in data engineering or related roles
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Strong expertise in SQL and programming languages such as Python, Scala, or Java
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Hands-on experience with big data technologies (Spark, Hadoop, Kafka, etc.)
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Experience with cloud platforms (AWS, Azure, or GCP)
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Proficiency in building and maintaining data pipelines and ETL tools (Airflow, dbt, etc.)
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Experience with data warehousing solutions (Snowflake, Redshift, BigQuery)
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Strong understanding of data modeling and database design
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Familiarity with CI/CD pipelines and DevOps practices
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Experience leading or managing a team
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Knowledge of data governance, security, and compliance standards
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Experience working in Agile/Scrum environments
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Exposure to real-time data processing and streaming architectures
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Certifications in cloud platforms or data engineering
