Data Integration Lead - ETL/Informatica

Key Responsibilities :

- Lead the design, development, and execution of enterprise-scale data integration strategies and architectures.

- Manage and govern data integration platforms, ensuring compliance with organizational and regulatory standards.

- Oversee the design and implementation of ETL/ELT processes, ensuring data quality, integrity, and performance.

- Collaborate with business stakeholders, data architects, and engineering teams to define integration requirements and deliver robust solutions.

- Manage, mentor, and guide a team of data integration engineers/developers, fostering a culture of best practices and innovation.

- Ensure scalability, reusability, and performance of integration solutions to meet growing business needs.

- Evaluate, recommend, and implement data integration tools and technologies aligned with enterprise goals.

- Partner with cloud platform teams to manage and optimize data pipelines across Azure, AWS, or GCP environments.

- Drive continuous improvement of integration practices, including monitoring, logging, automation, and operational support.

- Act as the platform governance owner, defining standards, guidelines, and best practices for data integration.

Required Skills & Qualifications :

- Bachelors/Masters degree in Computer Science, Information Systems, Data Engineering, or related field.

- 812 years of overall experience in data integration, data engineering, or related fields.

- 2+ years of proven leadership/managerial experience in leading data integration or data engineering teams.

- Deep expertise in ETL/ELT frameworks and tools (e.g., Informatica, Talend, SSIS, Azure Data Factory, AWS Glue, dbt).

- Strong experience in designing and managing data integration platforms and pipelines.

- Solid knowledge of integration architecture, APIs, data streaming (Kafka, Spark), and workflow orchestration.

- Proficiency with cloud data platforms (Azure Synapse, AWS Redshift, Google BigQuery, Snowflake).

- Hands-on experience with data warehousing, data lakes, and data governance practices.

- Strong problem-solving and analytical skills with a focus on performance optimization.

- Excellent communication, leadership, and stakeholder management skills.

Good to Have :

- Experience with DevOps and CI/CD pipelines for data integration.

- Knowledge of Python or Scala for scripting and automation in data pipelines.

- Exposure to Master Data Management (MDM) and enterprise metadata management solutions.

- Familiarity with Agile methodologies and managing distributed teams.