Senior Data Engineer

Position Description
Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com.
Job Title: Data Engineer
Position: Senior Software Engineer
Experience: 7 - 12 Years
Category: Software Development/ Engineering
Shift: Hybrid - (1PM to 10 PM Shift)
Main location: Hyderabad
Position ID: J1025-1300
Employment Type: Full Time
Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 6 years of relevant experience.
Position Description: We are seeking a highly experienced and skilled Staff/Senior Data Engineer to join our growing data team. In this pivotal role, you will be instrumental in designing, building, and maintaining our robust data infrastructure, ensuring the availability, reliability, and scalability of our data pipelines. You will work closely with data scientists, analysts, and product teams to transform raw data into actionable insights that power our business. If you are passionate about data, enjoy solving complex technical challenges, and thrive in a fast-paced environment, we encourage you to apply.

Your future duties and responsibilities
• Design & Development: Lead the design, development, and implementation of scalable, high-performance, and reliable data pipelines using various ETL/ELT tools and programming languages (e.g., Python, Scala).
• Data Modeling: Develop and optimize data models (dimensional, relational, columnar) for efficient storage, retrieval, and analysis of large datasets.
• Infrastructure Management: Build, maintain, and optimize data warehousing solutions (e.g., Snowflake, Redshift, BigQuery, Databricks) and data lakes (e.g., S3, ADLS).
• Performance Optimization: Identify and resolve performance bottlenecks in data pipelines and queries, ensuring optimal data flow and accessibility.
• Data Governance & Quality: Implement and enforce data governance best practices, ensuring data quality, integrity, security, and compliance.
• Collaboration: Work closely with data scientists, data analysts, and product managers to understand data requirements and translate them into technical solutions.
• Automation: Automate data extraction, transformation, loading (ETL/ELT) processes, monitoring, and alerting.
• Mentorship & Leadership: Mentor junior data engineers, provide technical guidance, and contribute to the overall growth and best practices of the data engineering team.
• Innovation: Stay up-to-date with emerging data technologies and trends, evaluating and recommending new tools and approaches to improve our data platform.
Documentation: Create and maintain comprehensive documentation for data pipelines, models, and processes.

Required qualifications to be successful in this role
• Bachelors or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of professional experience as a Data Engineer, with a strong track record of designing and implementing complex data solutions.
• Expert proficiency in SQL for data manipulation, analysis, and optimization.
• Strong programming skills in Python for data engineering tasks.
• Extensive experience with cloud-based data platforms such as AWS (S3, Glue, Lambda, Redshift, EMR), Azure (Data Lake, Data Factory, Synapse), or GCP (BigQuery, Dataflow, Cloud Storage).
• Proven experience with data warehousing concepts and technologies (e.g., Snowflake, Redshift, BigQuery, Databricks).
• Solid understanding of ETL/ELT processes and tools.
• Experience with big data technologies like Spark, Hadoop, or Kafka.
• Familiarity with data modeling techniques (star schema, snowflake schema, 3NF).
• Experience with version control systems (e.g., Git).
• Excellent problem-solving skills and the ability to troubleshoot complex data issues.
• Strong communication and interpersonal skills to collaborate effectively with cross-functional teams.
• Bachelor's degree in Computer Science, Engineering, or a related quantitative field.