Position Summary
We are seeking a Technical Lead - Data Engineering with strong hands-on experience in Snowflake, dbt, advanced SQL, Python, data modeling, and modern ELT development.
The role will lead technical design and development of scalable data engineering solutions on the Snowflake platform. The individual will develop and maintain dbt transformation models, Eligible to workimize data pipelines, implement data quality and governance practices, and collaborate with data engineering, analytics, BI, and business stakeholders.
The role also includes technical guidance, design reviews, mentoring of data engineering team members, and coordination across onsite and offshore delivery teams.
Experience supporting Informatica-to-dbt conversion or modernization initiatives is required.
Key Responsibilities
Data Engineering & ELT Development
- Design, develop, and maintain scalable, production-grade ELT pipelines using Snowflake, dbt, SQL, and Python.
- Develop and maintain dbt models, tests, macros, documentation, and reusable data assets.
- Design data transformation solutions supporting analytics, reporting, and business requirements.
- Develop data extraction, transformation, and loading processes using Python and applicable data engineering technologies.
- Implement incremental models, snapshots, and other appropriate dbt strategies.
- Support scalable data warehouse and data mart development.
Snowflake Development & Eligible to workimization
- Develop and maintain data warehouse solutions using Snowflake.
- Write advanced SQL queries for data transformation and analysis.
- Eligible to workimize Snowflake queries, warehouse configurations, and dbt models for performance and cost efficiency.
- Apply appropriate Snowflake data-engineering and security practices.
- Troubleshoot database, pipeline, transformation, and performance issues.
Data Modeling
- Design and implement dimensional data models using established modeling methodologies.
- Apply appropriate approaches such as Kimball dimensional modeling and/or Data Vault, based on project requirements.
- Develop reusable and maintainable data structures for analytical workloads.
- Ensure data models support scalability, maintainability, data quality, and downstream reporting requirements.
dbt Development & Governance
- Develop and maintain dbt projects using dbt Core or dbt Cloud.
- Implement dbt tests and automated data-quality checks.
- Maintain dbt documentation and data lineage.
- Develop reusable macros and standardized transformation components.
- Establish and follow development standards for dbt projects.
- Support governance, data-quality, and observability practices.
Informatica-to-dbt Modernization
- Participate in or lead Informatica-to-dbt conversion and modernization initiatives.
- Analyze existing Informatica workflows, mappings, transformations, dependencies, and business rules.
- Translate applicable Informatica transformations and workflows into dbt-based solutions.
- Validate converted pipelines against source and target requirements.
- Support reconciliation, testing, defect resolution, and production migration activities.
CI/CD, DevOps & Version Control
- Implement and maintain Git-based development workflows for data engineering and dbt projects.
- Support CI/CD pipelines for automated testing, validation, and deployment.
- Collaborate with DevOps teams to integrate dbt deployments into established delivery processes.
- Apply appropriate branching, code-review, release, and deployment practices.
- Support automated testing and deployment across applicable environments.
Orchestration & Integration
- Integrate dbt and data transformation workflows with applicable orchestration tools.
- Coordinate dependencies between ingestion, transformation, validation, and downstream processes.
- Troubleshoot workflow and pipeline failures.
- Support integration with cloud data platforms and enterprise data systems.
Data Quality, Observability & Security
- Implement automated data-quality validation and testing.
- Support monitoring and observability of data pipelines and transformation workflows.
- Identify and resolve data-quality issues and pipeline failures.
- Apply appropriate data governance and security practices within Snowflake and associated platforms.
- Support data lineage and documentation requirements.
Technical Leadership
- Lead technical projects involving Snowflake, dbt, SQL, and Python from design through implementation.
- Conduct technical design reviews and provide recommendations on implementation approaches.
- Establish and promote applicable coding, modeling, testing, and development standards.
- Provide technical guidance to data engineering team members.
- Mentor team members on data engineering, dbt, Snowflake, SQL, and development practices.
- Support delivery coordination across onsite and offshore team members.
- Identify technical risks, dependencies, and implementation challenges and communicate them through established project processes.
Stakeholder Collaboration
- Collaborate with data engineering, BI, analytics, business, architecture, and technical teams.
- Gather and analyze technical requirements and translate them into data engineering solutions.
- Communicate technical approaches, dependencies, risks, and project status to relevant stakeholders.
- Participate in solution design discussions and technical feasibility assessments.
Required Qualifications
- Professional experience in Data Engineering, Analytics Engineering, or a closely related technical field.
- Strong hands-on experience with Snowflake.
- Strong hands-on experience with dbt Core or dbt Cloud.
- Advanced SQL development and Eligible to workimization skills.
- Strong Python development experience for data engineering and ETL/ELT processes.
- Experience designing and developing production-grade ELT pipelines.
- Experience with data warehousing and data modeling.
- Experience implementing dbt models, tests, macros, documentation, and reusable data assets.
- Experience with incremental models and/or snapshot strategies.
- Experience with Git-based version control.
- Experience with CI/CD and DevOps-driven deployment practices.
- Experience implementing data-quality testing and validation.
- Experience troubleshooting data pipelines and transformation processes.
- Demonstrated experience providing technical guidance or leading technical design activities.
- Hands-on experience with Informatica-to-dbt conversion or modernization.
Preferred Qualifications
- Experience with Kimball dimensional modeling.
- Experience with Data Vault modeling.
- Experience with dbt Cloud.
- Experience with Snowflake performance tuning and cost Eligible to workimization.
- Experience with data observability platforms or frameworks.
- Experience with cloud data platforms and cloud security concepts.
- Experience integrating dbt with orchestration platforms.
- Experience supporting enterprise data modernization initiatives.
- Experience coordinating technical delivery across onsite and offshore teams.
Core Technical Skills
Required:
- Snowflake
- dbt Core / dbt Cloud
- Advanced SQL
- Python
- Data Warehousing
- Data Modeling
- ELT / ETL
- Git
- CI/CD
- Data Quality
- Informatica-to-dbt Conversion
Preferred:
- Kimball
- Data Vault
- Data Observability
- Cloud Data Platforms
- Data Governance
- Workflow Orchestration
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