Deloitte
Deputy Manager | Data Engineering | Hyderabad | Engineering as a Service/ Operate
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5+ years of hands-on experience in Data Engineering and cloud-based data solutions.
- Strong expertise in AWS, Azure, or Google Cloud Platform.
- Experience designing and implementing Data Lakes.
- Hands-on experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar ETL tools.
- Experience with serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions).
- Strong understanding of data governance, data quality, security, and compliance.
- Experience with Docker and Kubernetes.
- Strong programming skills in SQL, Python, Scala, or Java.
- Experience with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse.
- Proven leadership experience managing technical teams and delivering projects from pre-sales through implementation.
- Excellent communication and stakeholder management skills.
Nice to have
- Experience with AWS Lake Formation, Azure Purview, or Google Data Catalog.
- Cloud certifications (AWS, Azure, or GCP).
- Experience with CI/CD pipelines and DevOps practices.
Full description
Deputy Manager | Data EngineeringJob Title: Data Engineering Lead
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
- Lead the design and implementation of scalable cloud-based data engineering solutions and data lakes.
- Drive pre-sales activities, including client discussions, solution design, technical proposals, and Proof of Concepts (PoCs).
- Design secure and scalable data storage architectures using AWS, Azure, or GCP.
- Build and optimize ETL/ELT pipelines using Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar technologies.
- Develop efficient data transformation and processing workflows using serverless technologies such as AWS Lambda, Azure Functions, or Google Cloud Functions.
- Implement data governance, security, and data quality frameworks.
- Collaborate with data scientists, BI teams, and business stakeholders to enable reliable analytics.
- Lead and mentor a team of data engineers throughout the project lifecycle.
- Optimize cloud infrastructure, storage, and processing costs while maintaining performance and reliability.
- Ensure successful project delivery aligned with client and business objectives.
Required Skills
- 5+ years of hands-on experience in Data Engineering and cloud-based data solutions.
- Strong expertise in AWS, Azure, or Google Cloud Platform.
- Experience designing and implementing Data Lakes.
- Hands-on experience with Apache Spark, Databricks, AWS Glue, Azure Data Factory, or similar ETL tools.
- Experience with serverless computing (AWS Lambda, Azure Functions, Google Cloud Functions).
- Strong understanding of data governance, data quality, security, and compliance.
- Experience with Docker and Kubernetes.
- Strong programming skills in SQL, Python, Scala, or Java.
- Experience with cloud data warehouses such as Amazon Redshift, Google BigQuery, or Azure Synapse.
- Proven leadership experience managing technical teams and delivering projects from pre-sales through implementation.