Sr Manager Data Engineer

Organization:- Leading Global Management Consulting Organization (One of the BIG 3)

Role :- Data Engineering Sr Manager

Location :- Gurugram

Exp:- 10 + Years

Skills :- 70% hands on technical + 30% People management

What You'll Do

As a Senior Manager - Data Engineering to spearhead our data engineering team that focuses on building and maintaining HR functional data products. This role involves leading a medium-sized data engineering squad and delivering top-tier foundational capabilities and developing data products that enhance decision-making, provide new insights, ensure operational excellence, and reduce firm risks.

The creation of strategic, well-constructed and integrated Data Products as per our enterprise-wide Data strategy is important for us to deliver the most important Business Intelligence, Advanced Analytics, Data Science and Operational use cases. In this context, establishing a robust, scalable, and highly performant ETL pipeline is critical, given the extensive use of the data that goes through these pipelines and is used by a wide range of organizational units and teams.

This is a senior and highly visible role that requires a mix of technical acumen and leadership skills to drive the next generation of the organization's data and analytics ecosystem. This person must be creative, ask questions, and be comfortable challenging the status quo and must have very good communication skills with proven experience in stakeholder engagement, including senior business & tech teams.

What You'll Bring

Essential Education

• Minimum of a Bachelor's degree in Computer Science Engineering or a similar field
• Additional Certification in Data Management or cloud data platforms like Snowflake is preferred

Essential Experience & Job Requirements

• 12+ years of IT experience with a major focus on data warehouse-related projects, BI/Analytical systems, Data cataloguing, MDM, etc, is required
• Expertise in cloud databases like Snowflake, Redshift, etc, is required
• Proficiency in Conceptual, Logical, and Physical Data Modelling for both transactional (OLTP) and analytical (OLAP) purposes is a must.
• Proficiency in Data Management, ETL/ELT and data analytics tools like AWS Glue, DBT, FiveTran, Tableau, Power BI, etc is required
• Proficiency in Workflow Orchestration tools like Apache Airflow or Azure Data Factory is required.
• Knowledge of APIs and understanding distributed systems is also necessary for integrating different data sources and handling large datasets.
• Excellent written, oral communication and presentation skills to present architecture, features, and solution recommendations are a must
• Proficiency in languages like Python is essential for data processing, automation, and pipeline development
• Experience in building HR Data Solutions to support Comp Benchmarking, Pay Transparency / Pay Equity and Total Rewards use cases preferred.
• Experience with Cloud Big Data technologies such as AWS, Azure, GCP is a plus
• Experience working with agile methodologies (Scrum, Kanban) and Meta Scrum with cross-functional teams (Product Owners, Scrum Master, Architects, and data SMEs) is a plus

YOURE GOOD AT

• Extensive experience in large Data Engineering projects, methodologies, and concepts related to crafting and implementing intricate ETL pipelines, encompassing data ingestion, processing, and storage.
• Demonstrated success in building a top-performing data engineering team, with substantial and verified expertise in identifying, embracing, and advocating for best practices in data engineering and the development of enterprise data warehouses through extensive and intricate data/ETL pipelines
• Led end-to-end vision on how business requirements translate into technical specifications, including data streams, integrations, transformations, databases, and data warehouses
• Collaborate with product owners and business stakeholders to develop a data product, a data engineering and a delivery roadmap at the enterprise level
• Led design and implementation of numerous complex data flows from Custom and SAAS Platforms, Snowflake and AWS data services for analytics and business intelligence (BI) systems