Data Engineer Requirement

Hello Team,

Reaching out to you for the requirement of Data Engineer 7 + years experience, No GAP in work history of 7 years relevant experience. BGV will be required or will have to be done for the candidate. This is a remote opportunity and hence bench resources are to be invited for the interview for this position. The opening is for 2 candidates. 
Kindly, submit 2 profiles from your end which fit the criteria mentioned above and has the following expertise in the data engineering domain.

Data Engineer:

• Lead the end-to-end technical design and execution of migration from Snowflake/Glue to DBT.
• Define and govern the data architecture across landing, bronze, silver, and gold layers on DBT.
• Translate business and source system logic into modular, well-documented DBT models.
• Guide Python-based ETL pipeline development and ensure output parity with legacy Snowflake pipelines.
• Drive technical decisions on partitioning, optimization, and performance tuning in Spark/DBT.
• Collaborate with client architects, data stewards, and QA teams to validate migration fidelity.
• Mentor and technically review work from India-based Data Engineers.
• Facilitate sprint planning, technical reviews, and architecture walkthroughs with client stakeholders.
• Proactively identify scope risks, dependencies, and technical blockers and communicate remediation plans.
• Ensure compliance with data governance, security, and access control standards.

Key Responsibilities

• Design, develop, and maintain modular DBT models following industry best practices.
• Build scalable transformation pipelines using DBT Core or DBT Cloud.
• Convert complex business requirements into reusable SQL models.
• Develop incremental models, snapshots, seeds, and macros.
• Create and maintain DBT source configurations and model documentation.
• Implement comprehensive data quality tests using built-in and custom DBT tests.
• Optimize model execution performance and dependency management.
• Design dimensional models including facts, dimensions, and aggregate tables.
• Implement Medallion Architecture (Bronze, Silver, Gold) using DBT transformations.
• Perform query optimization and improve warehouse performance.
• Participate in code reviews and enforce DBT development standards.
• Collaborate with Data Engineers, Data Architects, BI Developers, and Business Analysts.
• Support CI/CD deployment pipelines for DBT projects.
• Troubleshoot production issues and resolve data pipeline failures.

Core DBT Skills

• DBT Core / DBT Cloud (3+ Years)
• Advanced DBT Model Development
• Incremental Models
• Snapshots
• Seeds
• Macros & Jinja Templates
• Source Configuration
• Model Documentation
• Data Lineage Management
• Package Management
• Custom DBT Tests
• Schema.yml Configuration
• Project Structure & Best Practices

SQL & Data Transformation

• Advanced SQL (4+ Years)
• Complex Joins
• Common Table Expressions (CTEs)
• Window Functions
• Stored Procedures (Preferred)
• Query Optimization
• Execution Plan Analysis
• Data Cleansing & Transformation

Data Modeling

• Dimensional Data Modeling
• Star Schema
• Snowflake Schema
• Fact & Dimension Tables
• Slowly Changing Dimensions (SCD Type 1 & 2)
• Data Vault (Preferred)
• Medallion Architecture

Cloud Data Warehousing

Hands-on experience with one or more:

• Snowflake
• Databricks SQL Warehouse
• Google BigQuery
• Amazon Redshift
• Azure Synapse Analytics

Data Quality & Governance

• Data Validation
• Data Quality Frameworks
• DBT Tests
• Source Freshness Checks
• Schema Enforcement
• Metadata Management
• Data Lineage
• Documentation Standards

CI/CD & DevOps

• Git
• GitHub / GitLab / Azure DevOps
• CI/CD Pipelines
• Environment Management (Dev, QA, Prod)
• Version Control Best Practices
• Deployment Automation

Preferred Technical Skills

• Python (Good to Have)
• Apache Airflow
• Apache Spark (Preferred)
• Snowflake
• Databricks
• AWS / Azure / GCP Exposure
• REST APIs

Soft Skills

• Strong Analytical Thinking
• Problem Solving
• Excellent SQL Debugging Skills
• Technical Documentation
• Cross-functional Collaboration
• Code Review & Mentoring

Preferred Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
• Experience with modern ELT architectures.
• Hands-on experience with DBT Cloud deployment workflows.
• Familiarity with Agile/Scrum methodologies.

Nice to Have

• Experience migrating legacy ETL pipelines to DBT.
• Knowledge of Apache Airflow or Azure Data Factory orchestration.
• Experience with BI tools such as Power BI, Tableau, or Looker.
• Exposure to data observability tools like Great Expectations or Monte Carlo.