Job Title:  T&T | Engineering | Senior Consultant | Snowflake Data Engineer| Hyderabad

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning. 

Your work profile:

The Snowflake data engineer is responsible for managing client relationships and overseeing the successful delivery of programs or accounts. This role serves as the primary point of contact between the organization and its clients, ensuring alignment of goals, timelines, budgets, and expected outcomes while driving client satisfaction and business growth.

Key Skills & Competencies

• 5–8 Years of experience as a snowflake data engineer, developing and maintaining Snowflake data warehouse and Lakehouse components, including databases, schemas, tables, views, stages, file formats, and secure data access patterns.
•  Substantial hands-on experience delivering production-grade Snowflake platforms and complex data engineering solutions at enterprise scale.
• Advanced SQL expertise, including complex transformations, query profiling, performance diagnosis, and optimization of high-volume workloads.
• Strong Python engineering skills for reusable data-processing components, automation, API integration, testing, and operational tooling.
• Demonstrated experience designing and operating ELT/ETL and orchestration solutions using tools such as dbt, Airflow, Informatica, Matillion, Fivetran, Talend, Azure Data Factory, or AWS Glue.
• Strong experience with at least one cloud ecosystem: AWS (S3, Glue, Lambda, EMR), Azure (ADLS Gen2, ADF, Synapse, Databricks), or GCP (GCS, Dataflow, Dataproc, Pub/Sub).
• Experience implementing CI/CD, automated testing, Git-based development workflows, infrastructure as code, and secure cloud engineering practices.
• Ability to lead technical discussions, make architecture trade-offs explicit, communicate risks, and guide engineers through complex delivery challenges.
•  Experience with Snowflake cost governance, resource monitors, workload isolation, account-level controls, and platform usage analytics.
•  Exposure to Snowflake performance features and advanced platform patterns, including dynamic data refresh, secure sharing, and cross-environment promotion.
• Own the technical design and implementation of complex Snowflake data solutions, including ingestion patterns, transformation layers, data models, workload design, and platform integration.
• Design robust batch, incremental, and near-real-time ELT/ETL pipelines for structured and semi-structured data using Snowflake, SQL, Python, and enterprise integration/orchestration tools.
• Select and implement appropriate Snowflake capabilities—including Snowpipe, Streams and Tasks, Dynamic Tables, External Tables, Time Travel, Zero-Copy Cloning, and secure Data Sharing—based on workload and architectural requirements.

Preferred Qualifications

• Bachelor’s or Master’s degree in computer science, Engineering, Information Systems, or a related discipline.
• Relevant professional experience demonstrates both hands-on technical depth and ownership of complex data engineering outcomes.

Success Metrics

• Strong experience with at least one cloud ecosystem: AWS (S3, Glue, Lambda, EMR), Azure (ADLS Gen2, ADF, Synapse, Databricks), or GCP (GCS, Dataflow, Dataproc, Pub/Sub).
• Lead code reviews, technical design reviews, testing strategy, CI/CD implementation, and infrastructure-as-code practices using Git and tools such as Terraform.
• Design robust batch, incremental, and near-real-time ELT/ETL pipelines for structured and semi-structured data using Snowflake, SQL, Python, and enterprise integration/orchestration tools.
• Advanced SQL expertise, including complex transformations, query profiling, performance diagnosis, and optimization of high-volume workloads.
• Strong Python engineering skills for reusable data-processing components, automation, API integration, testing, and operational tooling.
• Demonstrated experience designing and operating ELT/ETL and orchestration solutions using tools such as dbt, Airflow, Informatica, Matillion, Fivetran, Talend, Azure Data Factory, or AWS Glue.
• SnowPro Advanced or relevant cloud/data engineering certifications.

Location and way of working:

• Base location: Hyderabad
• This profile involves occasional travelling to client locations.
• Hybrid is our default way of working. Each domain has customized the hybrid approach to their unique needs.