Practice Lead - Data Engineering (18-24 yrs)

This typically entails leading and overseeing a team of data engineers, defining the overall data architecture strategy, building scalable data pipelines, ensuring data quality and governance, collaborating with cross-functional teams to drive data-driven decision making, and managing the technical roadmap for data engineering initiatives within an organization; requiring extensive experience in data engineering technologies, strong leadership skills, and a deep understanding of business needs to translate them into technical solutions.

Key Responsibilities :

- Strategic Leadership :

- Develop and execute a comprehensive data engineering strategy aligned with business objectives, including data architecture, data pipelines, and data governance policies.

- Define the long-term vision for data infrastructure, identifying opportunities for modernization and innovation.

- Collaborate with senior stakeholders across departments to understand data needs and translate them into actionable data engineering plans.

Team Management :

- Build, lead, and mentor a high-performing team of data engineers, including recruiting, performance management, and career development.

- Foster a culture of collaboration, innovation, and continuous improvement within the data engineering team.

- Establish clear technical standards, best practices, and coding guidelines for data engineering project

Technical Execution :

- Design and implement scalable data pipelines for data ingestion, transformation, and loading (ETL/ELT) across various data sources.

- Architect and manage data warehouses, data lakes, and other data storage solutions on cloud platforms (AWS, Azure, GCP).

- Oversee the development and maintenance of data quality monitoring systems to ensure data accuracy and reliability.

Data Governance :

- Establish data governance frameworks to manage data access, security, privacy, and compliance regulations.

- Define data ownership and accountability across the organization.

- Implement data quality checks and remediation processes.

Collaboration and Stakeholder Management :

- Partner with data scientists, analysts, product managers, and business leaders to understand their data needs and deliver data-driven insights.

- Communicate complex technical concepts effectively to both technical and non-technical audiences.

- Advocate for data-driven decision making across the organization.

Required Skills and Experience :

Technical Expertise :

- Deep understanding of data engineering principles, including data warehousing, data lakes, data pipelines, and distributed computing frameworks (Spark, Hadoop).

- Proficiency in cloud computing platforms (AWS, Azure, GCP) and related data services

- Experience with data modeling, data integration, and ETL/ELT processes

- Knowledge of data quality tools and techniques

Leadership Skills :

- Proven track record of leading and managing high-performing data engineering teams

- Excellent communication and collaboration skills to work effectively with cross-functional teams

- Ability to set clear expectations, provide constructive feedback, and drive team performancc

Business Acumen :

- Understanding of business needs and ability to translate them into data engineering solutions

- Strategic thinking and ability to align data engineering initiatives with overall business objectives

Education and Experience :

- Bachelor's degree in Computer Science, Engineering, or a related field

- 10+ years of experience in data engineering, with significant experience leading large data engineering teams

- Demonstrated experience in building and managing complex data infrastructure on cloud platforms