Job Title: Data Engineering Lead
Location: Bengaluru
Experience: 8 Years
About the Role
We are looking for a hands-on Data Engineering Lead to lead the design, implementation, and delivery of large-scale cloud-based data engineering solutions. The ideal candidate will have strong expertise in data lakes, cloud platforms, ETL/ELT pipelines, and modern data architecture while managing technical teams and client engagements from pre-sales through project delivery.
Key Responsibilities
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Lead the design and implementation of scalable cloud-based data engineering solutions and data lakes.
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Drive pre-sales activities, including client discussions, solution design, technical proposals, and Proof of Concepts (PoCs).
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Design secure and scalable data storage architectures using AWS, Azure, or GCP.
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Build and optimize ETL/ELT pipelines using Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar technologies.
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Develop efficient data transformation and processing workflows using serverless technologies such as AWS Lambda, Azure Functions, or Google Cloud Functions.
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Implement data governance, security, and data quality frameworks.
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Collaborate with data scientists, BI teams, and business stakeholders to enable reliable analytics.
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Lead and mentor a team of data engineers throughout the project lifecycle.
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Optimize cloud infrastructure, storage, and processing costs while maintaining performance and reliability.
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Ensure successful project delivery aligned with client and business objectives.
Required Skills
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5+ years of hands-on experience in Data Engineering and cloud-based data solutions.
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Strong expertise in AWS, Azure, or Google Cloud Platform.
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Experience designing and implementing Data Lakes.
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Hands-on experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar ETL tools.
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Experience with serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions).
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Strong understanding of data governance, data quality, security, and compliance.
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Experience with Docker and Kubernetes.
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Strong programming skills in SQL, Python, Scala, or Java.
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Experience with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse.
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Proven leadership experience managing technical teams and delivering projects from pre-sales through implementation.
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Excellent communication and stakeholder management skills.
Preferred Qualifications
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Experience with AWS Lake Formation, Azure Purview, or Google Data Catalog.
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Cloud certifications (AWS, Azure, or GCP).
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Experience with CI/CD pipelines and DevOps practices.
