Data Engineer

Job Title: Data Engineer (Snowflake + dbt)

Location: Hyderabad, India

Job Type: Full-time

Job Description:

We are looking for an experienced and results-driven Data Engineer to join our growing Data Engineering team. The ideal candidate will be proficient in building scalable, high-performance data transformation pipelines using Snowflake and dbt, and able to effectively work in a consulting setup. In this role, you will be instrumental in ingesting, transforming, and delivering high-quality data to enable data-driven decision-making across the client's organization.

Key Responsibilities:

• Design and implement scalable ELT pipelines using dbt on Snowflake, following industry-accepted best practices.
• Build ingestion pipelines from various sources including relational databases, APIs, cloud storage, and flat files into Snowflake.
• Implement data modelling and transformation logic to support layered architecture (e.g., staging, intermediate, and mart layers or medallion architecture) to enable reliable and reusable data assets.
• Leverage orchestration tools (e.g., Airflow, dbt Cloud, or Azure Data Factory) to schedule and monitor data workflows.
• Apply dbt best practices: modular SQL development, testing, documentation, and version control.
• Perform performance optimizations in dbt/Snowflake through clustering, query profiling, materialization, partitioning, and efficient SQL design.
• Apply CI/CD and Git-based workflows for version-controlled deployments.
• Contribute to growing internal knowledge base of dbt macros, conventions, and testing frameworks.
• Collaborate with multiple stakeholders such as data analysts, data scientists, and data architects to understand requirements and deliver clean, validated datasets.
• Write well-documented, maintainable code using Git for version control and CI/CD processes.
• Participate in Agile ceremonies including sprint planning, stand-ups, and retrospectives.
• Support consulting engagements through clear documentation, demos, and delivery of client-ready solutions.

Required Qualifications:

• 3 to 5 years of experience in data engineering roles, with 2+ years of hands-on experience in Snowflake and dbt.
• Experience building and deploying dbt models in a production environment.
• Expert-level SQL and strong understanding of ELT principles. Strong understanding of ELT patterns and data modelling (Kimball/Dimensional preferred).
• Familiarity with data quality and validation techniques: dbt tests, dbt docs, etc.
• Experience with Git, CI/CD, and deployment workflows in a team setting.
• Familiarity with orchestrating workflows using tools like dbt Cloud, Airflow, or Azure Data Factory.

Core Competencies:

Data Engineering and ELT Development:

• Building robust and modular data pipelines using dbt.
• Writing efficient SQL for data transformation and performance tuning in Snowflake.
• Managing environments, sources, and deployment pipelines in dbt.

Cloud Data Platform Expertise:

• Strong proficiency with Snowflake: warehouse sizing, query profiling, data loading, and performance optimization.
• Experience working with cloud storage (Azure Data Lake, AWS S3, or GCS) for ingestion and external stages.

Technical Toolset:

• Languages & Frameworks:
• Python: For data transformation, notebook development, automation.
• SQL: Strong grasp of SQL for querying and performance tuning.

Best Practices and Standards:

• Knowledge of modern data architecture concepts including layered architecture (e.g., staging → intermediate → marts, Medallion architecture).
• Familiarity with data quality, unit testing (dbt tests), and documentation (dbt docs).

Security & Governance:

• Access and Permissions:
• Understanding of access control within Snowflake (RBAC), role hierarchies, and secure data handling.
• Familiar with data privacy policies (GDPR basics), encryption at rest/in transit.

Deployment & Monitoring:

• DevOps and Automation:
• Version control using Git, experience with CI/CD practices in a data context.
• Monitoring and logging of pipeline executions, alerting on failures.

Soft Skills:

• Communication & Collaboration:
• Ability to present solutions and handle client demos/discussions.
• Work closely with onshore and offshore teams of analysts, data scientists, and architects.
• Ability to document pipelines and transformations clearly.
• Basic Agile/Scrum familiarity – working in sprints and logging tasks.
• Comfort with ambiguity, competing priorities, and fast-changing client environment.

Nice to Have:

• Experience in client-facing roles or consulting engagements.
• Exposure to AI/ML data pipelines, feature stores.
• Exposure to ML flow for basic ML model tracking.
• Experience/Exposure using Data quality tooling.

Education:

• Bachelor's or master's degree in computer science, Data Engineering, or a related field.
• Certifications such as Snowflake SnowPro, dbt Certified Developer Data Engineering are a plus.

Why Join Us?

• Opportunity to work on diverse and challenging projects in a consulting environment.
• Collaborative work culture that values innovation and curiosity.
• Access to cutting-edge technologies and a focus on professional development.
• Competitive compensation and benefits package.
• Be part of a dynamic team delivering impactful data solutions.

About Us:

Logic Pursuits provides companies with innovative technology solutions for everyday business problems. Our passion is to help clients become intelligent, information-driven organizations, where fact-based decision-making is embedded into daily operations, leading to better processes and outcomes. Our team combines strategic consulting services with growth-enabling technologies to evaluate risk, manage data, and leverage AI and automated processes more effectively. With deep, big four consulting experience in business transformation and efficient processes, Logic Pursuits is a game-changer in any operations strategy.