Lead Snowflake Data Engineer

Onusworks Software India; Bengaluru; Hybrid; INR 3,500,000 - 5,500,000; Full time

Job summary

Onusworks Software India in Bengaluru seeks a Lead Data Engineer with 8+ years of experience to design and build scalable data platforms using Snowflake and dbt. You will own end-to-end data pipelines, optimize performance, and mentor junior engineers while engaging with customers to translate requirements into technical solutions.

You will drive data modelling, data migration initiatives, and robust ETL/ELT processes across enterprise data warehouses, ensuring data quality, governance, and cost

Qualifications

• Extensive hands-on experience with Snowflake, dbt, SQL, ETL/ELT.
• Experience leading end-to-end data engineering projects.
• Ability to work directly with customers and translate requirements.

Responsibilities

• Lead design and development of scalable data solutions using Snowflake and dbt.
• Develop and optimize complex SQL queries and data pipelines.
• Design ETL/ELT processes and oversee data migration initiatives.
• Own source-to-target mappings, data validation, and reconciliation.
• Mentor junior/mid-level engineers and drive best practices.

Skills

Snowflake

dbt

SQL

ETL/ELT

Data Modeling

Data Warehousing

Data Migration

Tools

Git

CI/CD

Airflow

Power BI

Job description

Job Description: Lead Data Engineer Snowflake & DBT

Experience: 8+ Years

Role: Lead Data Engineer Employment Type: Full-Time

Job Summary

We are looking for an experienced Lead Data Engineer with strong hands-on expertise in Snowflake, dbt, ETL/ELT development, data migration, and data modelling. The ideal candidate will have a proven track record of designing and implementing scalable data engineering solutions, leading complex technical deliverables, and optimizing enterprise data warehouse platforms.

The candidate must be comfortable working directly with customers and business stakeholders, translating business requirements into technical solutions, and independently driving development activities from requirement gathering through implementation. This is a hands‑on individual contributor role that requires technical ownership, solution design capabilities, and the ability to mentor team members when required.

Key Responsibilities

• Lead the design, development, and implementation of scalable data engineering solutions using Snowflake and dbt.
• Develop and optimize complex SQL queries, stored procedures, views, and Snowflake data transformation pipelines.
• Design and implement efficient ETL/ELT processes to ingest, transform, and integrate data from multiple source systems.
• Lead data migration initiatives from legacy databases, on‑premises data warehouses, and other platforms to Snowflake.
• Define source‑to‑target mappings, transformation logic, migration strategies, data validation, and reconciliation processes.
• Design and implement robust data models, including conceptual, logical, physical, and dimensional models.
• Develop reusable dbt models, macros, tests, snapshots, documentation, and incremental data processing workflows.
• Optimize Snowflake query performance, warehouse utilization, scalability, and compute costs.
• Establish data engineering best practices, coding standards, reusable frameworks, and deployment processes.
• Implement data quality checks, monitoring, error handling, and data reconciliation mechanisms.
• Work directly with customers and business stakeholders to gather requirements, clarify business rules, and recommend technical solutions.
• Translate functional and business requirements into technical designs and implementation plans.
• Take end‑to‑end ownership of assigned deliverables, resolve complex technical issues, and ensure timely delivery.
• Collaborate with data architects, analytics teams, application teams, and business users.
• Conduct code reviews, provide technical guidance, and mentor junior and mid‑level data engineers as needed.
• Support production deployments, troubleshoot data pipeline failures, and ensure data platform reliability.
• Follow data security, governance, access control, and enterprise development standards.

Mandatory Technical Skills

1. Snowflake

• Strong hands‑on experience designing and developing solutions on Snowflake.
• Expertise in Snowflake SQL, query optimization, performance tuning, and cost optimization.
• Experience with virtual warehouses, stages, file formats, streams, tasks, and Snowflake data ingestion capabilities.
• Understanding of Snowflake architecture, workload management, and scalable data processing.
• Experience designing secure, reliable, and high‑performance data warehouse solutions.

2. dbt (Data Build Tool)

• Strong hands‑on experience developing and managing enterprise dbt projects.
• Expertise in dbt models, macros, materializations, snapshots, tests, and documentation.
• Experience with incremental models, dependency management, reusable transformations, and modular project design.
• Ability to implement data quality checks and maintainable transformation frameworks.
• Experience integrating dbt with Snowflake and managing code through Git‑based workflows.

3. ETL/ELT Development

• Strong understanding of ETL/ELT architecture and data integration patterns.
• Experience designing and implementing complex, scalable data pipelines.
• Knowledge of batch and incremental data processing.
• Experience with pipeline orchestration, scheduling, monitoring, error handling, and recovery mechanisms.
• Ability to troubleshoot performance and data consistency issues across the data pipeline lifecycle.

4. Data Migration

• Proven experience leading or owning data migration projects involving Snowflake.
• Experience migrating data from legacy databases, on‑premises systems, or other cloud data platforms.
• Strong understanding of source‑to‑target mapping, data profiling, transformation rules, and reconciliation.
• Experience planning migration phases, validating migrated data, resolving discrepancies, and supporting cutover activities.
• Ability to define migration approaches that minimize business disruption and maintain data integrity.

5. Data Modelling

• Strong knowledge of conceptual, logical, and physical data modelling.
• Expertise in dimensional modelling, star schemas, snowflake schemas, fact and dimension tables, and slowly changing dimensions (SCD).
• Ability to design scalable and maintainable data models aligned with business requirements.
• Understanding of data warehouse architecture, data integration patterns, and analytical data structures.
• Ability to review data models and recommend improvements for performance, usability, and maintainability.

6. SQL and Database Technologies

• Advanced SQL skills, including complex joins, CTEs, window functions, analytical functions, and query optimization.
• Strong understanding of relational database concepts, data warehousing, and data transformation techniques.
• Experience analysing complex data structures and troubleshooting data‑related issues.

Preferred Skills

• Experience with AWS, Microsoft Azure, or Google Cloud Platform.
• Exposure to orchestration tools such as Apache Airflow or equivalent platforms.
• Experience with Git, CI/CD pipelines, automated testing, and deployment practices.
• Knowledge of Python for data processing and automation.
• Familiarity with Power BI, Tableau, or other BI and reporting tools.
• Understanding of data governance, data lineage, metadata management, and enterprise data quality frameworks.
• Experience working in Agile delivery environments.

Required Experience and Competencies

• Minimum 8+ years of relevant experience in data engineering, data warehousing, or related technologies.
• Strong hands‑on expertise in Snowflake, dbt, SQL, ETL/ELT, data migration, and data modelling.
• Demonstrated experience owning complex technical deliverables and driving end‑to‑end implementations.
• Ability to work directly with customers and business stakeholders without continuous supervision.
• Strong technical design, analytical, troubleshooting, and problem‑solving skills.
• Excellent communication, stakeholder management, and requirement‑gathering capabilities.
• Ability to guide technical teams, conduct code reviews, and establish development best practices.
• Strong ownership, accountability, and commitment to delivery quality.