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Lead Data Engineer
Primary Skills
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 requirements
Job Title: Lead Data Engineer
Job Overview:
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.
Key Responsibilities:
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.
Required Skills & Experience:
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.
Preferred Qualifications:
GCP Professional Data Engineer certification.
Experience with tools like dbt, Terraform, or Kafka.
Background in analytics, machine learning pipelines, or DevOps for data.
Brillio is an equal opportunity employer to all, regardless of age, ancestry, colour, disability (mental and physical), exercising the right to family care and medical leave, gender, gender expression, gender identity, genetic information, marital status, medical condition, military or veteran status, national origin, political affiliation, race, religious creed, sex (includes pregnancy, childbirth, breastfeeding, and related medical conditions), and sexual orientation.
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