Job Title:  T&T | Engineering | 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 quality 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

• 4–6 Years of experience in developing and maintaining Snowflake data warehouse and Lakehouse components, including databases, schemas, tables, views, stages, file formats, and secure data access patterns.
• Build and operate batch and incremental ELT/ETL pipelines for structured and semi-structured data using SQL, Python, and suitable orchestration or integration tools.
• Implement Snowflake features such as Snowpipe, Streams and Tasks, Dynamic Tables, Time Travel, Zero-Copy Cloning, External Tables, and Data Sharing where appropriate.
• Develop reusable transformations, dimensional models, data marts, and source-to-target mappings; use dbt or equivalent frameworks where applicable.
• Integrate Snowflake with cloud storage and services on AWS, Azure, or GCP, including secure ingestion and data movement patterns.
• Troubleshoot pipeline failures, reconcile data, implement data quality checks, and support production incidents through root-cause analysis.
• Tune SQL queries and workloads; apply appropriate warehouse sizing, caching, clustering, and resource-monitoring practices to balance performance and cost.
• Implement role-based access control, masking, secure views, secrets handling, and other data protection controls in line with platform standards.
• Use Git, code reviews, automated testing, and CI/CD practices to deliver maintainable and production-ready data assets.
• Collaborate with data architects, analysts, QA, platform teams, and business stakeholders to clarify requirements and deliver tested solutions.
• Hands-on Snowflake development experience, including core platform objects, loading patterns, workload execution, and operational troubleshooting.
• Strong SQL skills, including complex joins, CTEs, window functions, query plans, and performance tuning.
• Working proficiency in Python for data processing, automation, API integration, or pipeline utilities.
• Practical experience with at least one ETL/ELT or orchestration tool, such as dbt, Airflow, Matillion, Fivetran, Informatica, Talend, Azure Data Factory, or AWS Glue.
• Experience with at least one cloud platform: AWS (S3, Glue, Lambda), Azure (ADLS Gen2, ADF, Databricks), or GCP (GCS, Dataflow, Pub/Sub).
• Understanding of relational databases such as Oracle, SQL Server, PostgreSQL, Teradata, or MySQL; familiarity with semi-structured formats such as JSON and Parquet.
• Familiarity with Git, code review, CI/CD, testing, logging, and secure cloud development practices.
• Ability to translate technical requirements into clear, tested data pipeline and transformation deliverables.
• Exposure to Databricks, Kafka or other event-streaming technologies, and lakehouse architectures.
• Familiarity with data governance, metadata, lineage, data catalogues, RBAC, and masking policies.
• Exposure to Terraform or other infrastructure-as-code tools.
• Awareness of AI/ML and GenAI data requirements, including curated datasets for analytics or retrieval-augmented generation (RAG).
• Banking and Financial Services domain experience is an advantage.

Preferred Qualifications

• Bachelor’s or Master’s degree in computer science, Engineering, Information Systems, or a related discipline.
• SnowPro Core and/or relevant AWS, Azure, or GCP certifications are preferred.

Success Metrics

• Reliable, well-tested pipelines delivered to agreed quality and schedule.
• Reduced data defects and production incidents through validation, monitoring, and root-cause fixes.
• Measurable improvements in query performance, pipeline efficiency, and Snowflake credit consumption.
• Clear documentation, reusable code, and adherence to security and engineering standards.
• SnowPro Core and/or relevant AWS, Azure, or GCP certifications are preferred.
• Hands-on Snowflake development experience, including core platform objects, loading patterns, workload execution, and operational troubleshooting.
• Strong SQL skills, including complex joins, CTEs, window functions, query plans, and performance tuning.
• Working proficiency in Python for data processing, automation, API integration, or pipeline utilities.

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.