About Us: We 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, which leads 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, It is a game-changer in any operations strategy.

Role: Senior Data Engineer (Snowflake & DBT)

Location: Hyderabad- (No Hybrid and No Work from Home available)
Budget: 18 - 22 LPA
Qualification: Bachelor's or master's degree in computer science, Data Engineering, or a related field.
Certifications: Certifications such as Snowflake SnowPro Advanced, BDT Certified Developer are a plus.
Experience: 6 - 10 Years experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and DBT in production environments
Communication skills: Please do not compromise on communication skills. (Must be excellent)
Mandatory Skills: Snowflake, DBT, Azure Data Factory, Python Programming, SQL, Medallion Architecture, Azure Data Lake, Jinja, Project Ownership, Team Handling, Performance Optimization, DBT Cloud, ETL/ELT, Security and Governance, HIPPA, RBAC
Notice period: We are looking for immediate joiners -15 Days only, We can add joining bonus for a very good candidate with immediate joiner.
Working days: This is 5 days work from office role- (No Hybrid and No Work from Home available)
Interview Rounds: There are 2 rounds in the interview process

Job Description

We are seeking a highly skilled and experienced Senior Data Engineer to join our growing data team. In this role, you will lead the design and implementation of scalable, high-performance data pipelines using Snowflake and dbt, define architectural best practices, and drive data transformation at scale. You'll work closely with clients to translate business needs into robust data solutions and play a key role in mentoring junior engineers, enforcing standards, and delivering production-grade data platforms.

Key Responsibilities

Architect and implement modular, test-driven ELT pipelines using DBT on Snowflake.
Design layered data models (e.g., staging, intermediate, mart layers / medallion architecture) aligned with DBT best practices.
Lead ingestion of structured and semi-structured data from APIs, flat files, cloud storage (Azure Data Lake, AWS S3), and databases into Snowflake.
Optimize Snowflake for performance and cost: warehouse sizing, clustering, materializations, query profiling, and credit monitoring.
Apply advanced DBT capabilities including macros, packages, custom tests, sources, exposures, and documentation using DBt docs.
Orchestrate workflows using DBT Cloud, Airflow, or Azure Data Factory, integrated with CI/CD pipelines.
Define and enforce data governance and compliance practices using Snowflake RBAC, secure data sharing, and encryption strategies.
Collaborate with analysts, data scientists, architects, and business stakeholders to deliver validated, business-ready data assets.
Mentor junior engineers, lead architectural/code reviews, and help establish reusable frameworks and standards.
Engage with clients to gather requirements, present solutions, and manage end-to-end project delivery in a consulting setup

Required Qualifications: 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and DBT in production environments.

Technical Skills

Cloud Data Warehouse & Transformation Stack:

Expert-level knowledge of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost management.
Experience in DBT development: modular model design, macros, tests, documentation, and version control using Git.

Orchestration And Integration

Proficiency in orchestrating workflows using DBT Cloud, Airflow, or Azure Data Factory.
Comfortable working with data ingestion from cloud storage (e.g., Azure Data Lake, AWS S3) and APIs.

Data Modelling And Architecture

Dimensional modelling (Star/Snowflake schemas), Slowly changing dimensions.
Knowledge of modern data warehousing principles.
Experience implementing Medallion Architecture (Bronze/Silver/Gold layers).
Experience working with Parquet, JSON, CSV, or other data formats.

Programming Languages

Python: For data transformation, notebook development, automation.
SQL: Strong grasp of SQL for querying and performance tuning.
Jinja (nice to have): Exposure to Jinja for advanced DBT development.

Data Engineering & Analytical Skills

ETL/ELT pipeline design and optimization.
Exposure to AI/ML data pipelines, feature stores, or MLflow for model tracking (good to have).
Exposure to data quality and validation frameworks.

Security & Governance

Experience implementing data quality checks using DBT tests.
Data encryption, secure key management and security best practices for Snowflake and DBT.

Soft Skills & Leadership

Ability to thrive in client-facing roles with competing/changing priorities and fast-paced delivery cycles.
Stakeholder Communication: Collaborate with business stakeholders to understand objectives and convert them into actionable data engineering designs.
Project Ownership: End-to-end delivery including design, implementation, and monitoring.
Mentorship: Guide junior engineers and establish best practices; Build new skill in the team.
Agile Practices: Work in sprints, participate in scrum ceremonies, story estimation.

Education

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

Why Join Us

Work on modern data architecture at scale using cutting-edge Azure technologies.
Collaborate with a dynamic and talented team of data professionals.
Grow your leadership skills through hands-on project ownership and mentorship.
Competitive compensation, flexible work options, and continuous learning culture.

Skills: etl/elt,snowflake and dbt,data engineering,dbt,python,snowflake,ai/ml data pipelines