National Consulting Services
The National Office, a key Strategic Enabler in our new model, is comprised of professionals with various areas of focus that collectively provide mission critical services to support Deloitte’s overall success. Whether focused on project financial, quality and risk management, methods and tools, sales excellence, talent, leadership support, or other activities these professionals ensure that our Firm operates efficiently, and our people are able to effectively serve clients every day.
Position Summary
Level: Consultant or equivalent
At Deloitte Consulting LLP, Data Engineers design, build, and optimize data ecosystems that transform raw information into business value. You will work with cloud technologies, distributed systems, and modern data architectures to enable analytics, AI, and decision-making across complex organizations.
What You’ll Do
- Design and implement data workflows using Medallion architecture (bronze, silver, gold layers), ensuring clean separation of raw, refined, and curated data to optimize quality and accessibility.
- Manage and process large, high-volume datasets efficiently, using best practices in performance optimization, partitioning, indexing, and resource utilization.
- Implement robust ETL/ELT processes to ingest, process, and integrate structured and unstructured data from diverse sources.
- Apply distributed computing principles to support high-volume, high-velocity data workflows, using industry-standard frameworks and cloud data platforms.
- Collaborate with analysts, data scientists, and business stakeholders to translate requirements into technical solutions.
- Ensure data quality, integrity, security, and effective data governance throughout the data lifecycle.
- Optimize and monitor data jobs for reliability, performance, and cost efficiency, proactively identifying and resolving bottlenecks or scalability constraints.
- Automate data engineering and operations tasks using modern programming languages (preferably Python, but others are considered).
- Produce clear, maintainable documentation for data architectures and workflow processes.
- Stay current with advancements in data engineering, cloud services, and big data technologies, and proactively recommend improvements.
The team:
IDT anticipates how technology will shape the future and begins building future capabilities and practices today. IDT drives the Ideation, Incubation and scale of hybrid businesses and tech enabled offerings at prioritized offering portfolio and industry interactions.
It drives cultural and capability transformation from solely services – based businesses to hybrid businesses. While others bet on the future, IDT builds it with you. IDT partners with the network such as converge, Small factory, True Serve, Cortex AI to build hybrid businesses, enterprise platforms and incubate emerging practices to future proof business and help clients get there, first. IDT encompasses many teams—dreamers, designers, builders—and partners with the business to bring a unique POV to deliver services and products for clients.
Qualifications
Must Have Skills/Project Experience/Certifications
- 2–5 years’ experience in data engineering, analytics, or related technical roles.
- Proven experience architecting and operating distributed data processing systems (e.g., Apache Spark, Hadoop, Dataflow, Databricks, or similar frameworks).
- Experience designing solutions using the Medallion architecture (bronze/silver/gold data layers) or similar multi-layer data organization patterns.
- Experience managing, transforming, and optimizing large-scale datasets for analytics, reporting, or machine learning use cases.
- Proficiency in ETL/ELT pipeline development and orchestration using tools such as Airflow, Data Factory, or equivalent.
- Strong coding skills in Python and/or Java/Scala for data manipulation and pipeline automation.
- Solid background in SQL and data modeling, with experience working with modern data warehouses (e.g., BigQuery, Synapse, Snowflake, Redshift).
- Demonstrated ability to optimize data solutions for performance and cost, including partitioning, caching, and efficient resource management.
- Understanding of data security, IAM, and governance practices.
- Effective verbal and written communication to articulate technical solutions to non-technical stakeholders.
Good to Have/Preferred Skills
- Hands-on experience with cloud data platforms, such as AWS, Azure, or GCP.
- Preference for candidates with GCP and BigQuery experience.
(Candidates with AWS/Azure or multi-cloud experience are also encouraged to apply.)
- Familiarity with DevOps/CI-CD in data environments, containerization (Docker/Kubernetes), and workflow automation tools.
- Experience supporting analytics or ML teams by preparing production-ready data pipelines and performing feature engineering.
Education
B.E./B.Tech./M.C.A./M.Sc./Ph.D. in Computer Science, Information Technology, or a related discipline.
Locations
Hyderabad / Bengaluru / Kolkata / Chennai / Pune.