Senior Manager

• Senior Manager (Data Engineering) Role Overview: The Role will be responsible for leading the analytics engagement for one of our Utilities clients
• We are looking for a high impact Analytics & Data Engineering leader to set the vision & strategy across business, customer, marketing & data analytics for client
• This position requires proven track record of data engineering, pipeline development, A Data Engineer is responsible for designing, building, and maintaining systems and infrastructure that enable organizations to collect, store, and analyze large volumes of data efficiently
• They work closely with data scientists, analysts, and other engineers to ensure that data is processed and stored in a way that supports analytics, machine learning, and business intelligence initiatives
• Key Responsibilities: Data Pipeline Development: Design, build, and maintain scalable and reliable data pipelines to collect, process, and transform raw data into usable formats
• Automate the movement and transformation of data across various systems and sources, ensuring data flows seamlessly
• Database Management: Create and maintain robust data storage solutions, including data warehouses, data lakes, and databases
• Ensure the database architecture is optimized for query performance, scalability, and security
• Handle data migrations, backups, and data restoration processes
• ETL (Extract, Transform, Load) Processes: Build and manage ETL pipelines to extract data from various sources, transform it to fit the needs of analytics and business intelligence, and load it into storage systems
• Ensure data quality and consistency throughout the ETL pipeline
• Data Modeling: Design and implement data models, schemas, and structures that efficiently store and retrieve data
• Work with stakeholders to ensure that the data model aligns with business requirements and optimizes performance
• Data Integration: Integrate data from multiple sources (internal and external) into a unified platform
• Ensure proper data mapping, transformation, and consolidation across systems
• Data Governance and Security: Implement data governance policies, including data lineage, data quality, and compliance (eg, GDPR, HIPAA)
• Work with security teams to ensure that data is securely stored and accessed
• Performance Optimization: Monitor and optimize data processing pipelines to handle increasing volumes of data efficiently
• Troubleshoot and resolve any performance bottlenecks in data processing and storage systems
• Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data needs and deliver solutions that support analytics, reporting, and machine learning efforts
• Collaborate with software engineers to integrate data systems with other software applications
• Required Skills: Programming Languages: Proficiency in languages such as Python and SQL Data Pipeline & Workflow Automation: Experience with tools like Apache Kafka, Apache Airflow, Luigi, or similar workflow management systems
• Databases & Data Warehousing: Knowledge of relational databases (MySQL, PostgreSQL), NoSQL databases (MongoDB, Cassandra), and cloud-based data warehouses (Redshift, BigQuery, Snowflake)
• Big Data Technologies: Familiarity with big data platforms like Hadoop, Spark, and Hive
• Cloud Platforms: Experience with cloud services such as AWS, Google Cloud, or Azure for data storage, processing, and analytics
• Data Modeling & Architecture: Experience in designing data models, schemas, and data storage architectures
• Version Control Systems: Proficiency in Git and versioning tools for managing data workflows
• Data Quality & Governance: Understanding of data quality management, data validation, and governance frameworks

Candidate Profile:

• Educational Qualifications: Typically a degree in Computer Science, Information Technology, Data Science, or a related field
• Experience: 5+ years of experience in data engineering, data management, or software engineering with a focus on data systems
• Certifications: Certifications in cloud platforms (AWS, Azure, GCP) or big data technologies can be beneficial
• Client Engagement Experience especially with senior stakeholders Effective communication and thought leadership with proven record Bachelor s/Masters degree in economics, mathematics, computer science/engineering or related analytics areas
• Prior experience in managing and delivering on end to end projects Outstanding written and verbal communication skills Able to work in fast pace continuously evolving environment and ready to take up uphill challenges Is able to understand cross cultural differences and can work with clients across the globe