HexaCorp - Lead Data Engineer - ETL (9-16 yrs)

About Lead Cloud Data Engineer:

As a Cloud Data Engineering Lead, you will play a pivotal role in designing, developing, and implementing robust data solutions for our clients. You will lead a team of data engineers to deliver high-quality data pipelines and data lakes, ensuring seamless integration with various data sources and business intelligence platforms.

Key Responsibilities :

- Design and implement scalable and efficient data architectures, including data warehouses, data lakes, and data marts.

- Define data models, schemas, and metadata standards.

- Collaborate with data analysts and business stakeholders to understand data requirements and translate them into technical specifications.

- Design and develop complex data integration pipelines using ETL/ELT tools (e.g., Informatica, Talend, Azure Data Factory, AWS Glue, Google Data Fusion).

- Extract, transform, and load data from various sources (e.g., databases, APIs, files) into target systems.

- Implement data quality checks and monitoring processes to ensure data accuracy and consistency.

- Leverage cloud platforms (Azure, AWS, GCP) to build and deploy data solutions.

- Utilize cloud-native data services (e.g., Azure Data Factory, AWS Glue, Google Data Fusion) for efficient data processing.

- Lead and mentor a team of data engineers.

- Assign tasks, provide guidance, and review deliverables.

- Foster a collaborative and innovative team culture.

- Interact with clients to understand their business needs and translate them into technical solutions.

- Present technical concepts to both technical and non-technical audiences.

- Keep abreast of the latest trends and technologies in data engineering and cloud computing.

- Continuously improve skills and knowledge through training and certifications.

Requirement :

- 9+ years of experience in data warehousing, data lakes, data integration, and ETL/ELT processes.

- Strong proficiency in at least one leading ETL/ELT tool (e.g., Informatica, Talend, Azure Data Factory, AWS Glue, Google Data Fusion).

- Experience with cloud platforms (Azure, AWS, GCP) and cloud-native data services.

- Solid understanding of data modeling, data warehousing concepts, and data quality principles.

- Proficiency in SQL and scripting languages (Python, Scala, etc.).

- Experience with data visualization tools (Power BI, Tableau, Looker).

- Strong problem-solving and analytical skills.

- Excellent communication and interpersonal skills.

- Ability to work independently and as part of a team.