Lead Data Engineer - R01553056

About Brillio:

Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.

Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.

Lead Data Engineer

• IICS, Alation, Data Modelling Fundamentals, Data Warehousing, ETL Fundamentals, Modern Data Platform Fundamentals, PLSQL, T-SQL, Stored Procedures, Python, SQL, SQL (Basic + Advanced), Talend

• Job Title: Lead Data Engineer

• We are seeking a highly skilled and experienced Senior Data Engineer to lead the development, migration, and optimization of data systems across our enterprise infrastructure.
• This role will play a critical part in migrating legacy data systems to Google BigQuery, designing robust ETL/data pipelines, and enabling real-time IoT data integration.
• The ideal candidate will have a strong background in cloud-based data warehousing, particularly in Google Cloud Platform (GCP), and deep expertise in Python, SQL, Spark, and data engineering best practices.

• 1. Data Migration & Cloud Modernization Analyze legacy on-premises and cloud data warehouse systems (e.g., SQL Server). Lead migration of large-scale datasets to Google BigQuery. Design and execute data migration strategies ensuring data quality, consistency, and performance.
• 2. Data Integration & Streaming Integrate data from diverse sources including APIs, relational databases, and unstructured data. Implement real-time streaming pipelines for IoT data ingestion and processing in large-scale environments.
• 3. ETL / Data Pipeline Development Evaluate and modernize legacy SSIS packages to cloud-native ETL pipelines. Design and develop scalable ETL workflows using Apache Airflow, Python, Spark, and other GCP-native tools. Ensure data is processed, transformed, and loaded reliably into BigQuery for downstream analytics.
• 4. Programming & Query Optimization Write complex SQL queries, stored procedures, and scheduled queries in BigQuery. Build reusable, modular data transformation scripts using Python, Java, Spark, and SQL. Optimize query performance and manage cost efficiency in a cloud data warehouse environment.

• 5+ years of experience in Data Engineering, including at least 2+ years working with Google Cloud Platform (GCP) and BigQuery.
• Strong experience with data migration from on-prem to cloud platforms. Proficiency in building ETL pipelines with Apache Airflow, Python, and Spark.
• Hands-on experience with streaming data ingestion (especially IoT data).
• Strong SQL development skills; experience with performance tuning in BigQuery.
• Solid understanding of cloud architecture and data warehouse design.
• Experience with version control systems (e.g., Git) and CI/CD for data pipelines.

• GCP Professional Data Engineer certification.
• Experience with tools like dbt, Terraform, or Kafka.
• Background in analytics, machine learning pipelines, or DevOps for data.

• #LI-SR1
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