Sr. Data Engineering Manager

We are inviting applications for a highly experienced and motivated Sr. Engineering Manager - Data Engineering.
In this role, you would be leading our data engineering team on multiple projects to success. Ideal candidate for this role should have around 15+ years of experience in the field of Data Engineering, Data Modeling, DWH, ETL, and BI. Candidate should provide efficient solutions, working together with customer stakeholders, onshore teams, and offshore teams, not compromising industry best practices, profitability, security and compliance, and evaluating new technologies/solutions as appropriate.

Roles & Responsibility

- Lead, mentor, and manage a team of data engineers to ensure successful delivery.
- Oversee the planning, execution, and delivery of data engineering projects.
- Ensure projects are delivered on time, within scope, and within budget utilizing Agile and SAFe methodologies.
- Design and architect scalable and efficient data systems for Business Intelligence or Data Warehouse, including data ingestion, ETL, and data integration using Azure DataBricks, Azure Synapse, Azure Data Factory, and Azure DevOps/Git.
- Oversee the maintenance and support of legacy data systems, including Hadoop, Diyotta, DataStage, and NiFi.
- Troubleshoot and resolve complex technical issues related to data systems.
- Lead the migration/modernization of legacy systems to modern data platforms, ensuring minimal disruption and maximum efficiency.
- Ensure high availability, reliability, and performance of data systems.
- Implement best practices for data architecture, data management, and data governance.
- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data needs and requirements.
- Provide technical guidance, mentorship, and roadmap to team members for constant upskilling/cross-skilling/certifications/bridge-gaps.

Technology & Architecture

Skills
- 15 years of experience in data engineering, with a strong focus on data lakes and big data technologies.
- Extensive experience with Azure DataBricks, Azure Synapse, Azure Data Factory, and Azure DevOps.
- Strong background in maintaining and supporting legacy systems, including Hadoop, Diyotta, NiFi, and DataStage.
- Sound knowledge in Hive, HDFS, Kafka, Sqoop, and Spark/PySpark.
- Proven experience in designing, architecting, Data Modeling, and migrating data systems.
- Excellent leadership, management, and mentoring skills.
- Strong project management skills, with the ability to manage multiple projects simultaneously.
- Excellent problem-solving skills and the ability to troubleshoot complex technical issues.
- Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams.
- Last but not the least, certifications in relevant technologies.

Good to have skills:
- Good knowledge of SQL, IBM DB2, Netezza.
- Experience with cloud platforms other than Azure (e.g., AWS, Google Cloud Platform).
- Experience in Cloud Data platforms like Snowflake.
- Experience with data governance and data security best practices.