Lead Data Engineer

Roles & Responsibilities:

• Designing and building optimized data pipelines using cutting-edge technologies in a cloud environment to drive analytical insights.
• Constructing infrastructure (on cloud - GCP) for efficient ETL processes from various sources and storage systems.
• Creating innovative data validation methods and data analysis tools.
• Ensuring compliance with data governance and security policies.
• Conducting complex data analysis and presenting results effectively.
• Continuously exploring opportunities to enhance data quality and reliability.

• Data Modeling:

oCreate and maintain data models that support business requirements and data analytics.

oEnsure data structures are optimized for performance and scalability.

• Collaboration:

oWork closely with cross-functional teams, including data scientists, analysts, and business users, to understand data needs and provide effective solutions.

oCollaborate with IT Infra team and security teams to ensure infra-availability, data privacy and compliance with security standards.

• Technology Knowledge:

ETL

oDevelop, optimize, and maintain ETL processes to extract, transform, and load data from diverse sources into the Data Lake.

Qliksense

oTalend knowledge is a minimum.

Datalake:

oDesign, implement, and maintain our Data Lake architecture to ensure efficient storage, retrieval, and processing of large volumes of structured and unstructured data.

Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.

oDremio or Google BigQuery knowledge would be an added advantage.

BI Integration:

oIntegrate Business Intelligence tools with the Data Lake to provide stakeholders with meaningful insights and reports.

oCollaborate with analysts and business users to understand reporting requirements and implement dashboards and visualizations.

oQlikSense or Tableau knowledge would be an added advantage.

Qualification and Skills:

• Bachelors degree in computer science, Information Systems, Data Science, or a related field.
• Minimum 6 to 7 years of experience in data engineering space
• Proficient in SQL to perform data querying and manipulation.
• Experience with data integration and ETL processes to extract, transform, and load data from various sources.
• Excellent verbal and written communication skills to effectively convey insights and findings to internal and external stakeholders.
• Strong problem-solving skills and the ability to find innovative solutions to business challenges through data visualization.
• Collaborative mindset with the ability to work effectively in a team-oriented environment.
• Strong analytical and critical-thinking skills to interpret data and draw meaningful conclusions.