#DFO&I2027
Customer
The Customer Team empowers organizations to build deeper relationships with customers through innovative strategies, advanced analytics, GenAI, transformative technologies, and creative design. We enable Deloitte client service teams to enhance customer experience and drive sustained growth and customer value creation and capture, through customer and commercial strategies, digital product and innovation, marketing, commerce, sales, and service. We are a team of strategists, data scientists, operators, creatives, designers, engineers, and architects, balancing business strategy, technology, creativity, and ongoing managed services to help solve the biggest problems that impact customers, partners, constituents, and the workforce. We also offer Business Process as a Service, enabling organizations to streamline operations and achieve greater efficiency through scalable, technology-enabled managed insights that guide ongoing transformation and operational excellence.
Position Summary-
Managed Services Engineer II or equivalent
As a Managed Services Engineer II at Deloitte Consulting, you will design, develop, and deploy enterprise-scale software solutions, lead the creation of robust pipelines and manage code deployment across environments. You will collaborate with cross-functional, global teams to translate functional requirements into effective deliverables, independently guiding and mentoring junior team members. Your role spans the full project lifecycle, including estimation, planning, execution, and tracking key metrics for analysis, ensuring high-quality and timely delivery of solutions.
Work you’ll do:
- Design, develop, and maintain scalable and reliable ETL/ELT pipelines using enterprise tools like Informatica and cloud-native services like Azure Data Factory.
- Lead and execute critical data migration projects, moving marketing and customer data from legacy systems to modern cloud platforms such as Snowflake or Databricks.
- Architect and implement data models within cloud data warehouses, ensuring data is optimized for performance, reliability, and accessibility for analytics and reporting.
- Write advanced, high-performance SQL and Python scripts to perform complex data transformations, build data validation frameworks, and ensure high data quality.
- Collaborate with cross-functional teams—including architects, developers, and marketing analysts—to gather requirements and deliver holistic data solutions.
- Engage in requirement gathering, solution design, and technical decision-making aligned with client marketing analytics goals.
- Support post-deployment activities, including pipeline maintenance, performance tuning, and client communication.
- Take ownership of your data engineering deliverables and proactively identify opportunities for improvement in client data architectures.
- Uphold Deloitte’s values of integrity, client focus, and making an impact that matters.
The team:
Our Digital Foundry Operate & Innovations (DFO&I) team partners with organizations to rapidly design, build, and scale digital products and experiences that drive business growth and elevate customer engagement. As a multidisciplinary group of strategists, designers, engineers, and operations specialists, we deliver end-to-end solutions—from initial concept and agile development to ongoing digital operations—enabling clients to experiment, iterate, and scale digital initiatives with confidence and agility. We support clients across domains such as strategy, commerce, marketing, sales, and service, helping them realize their digital ambitions through flexible, scalable teams. Our expertise spans the full digital lifecycle, including customer research, experience design, platform development, content production, and marketing automation. By bridging the gap between strategy and execution, we empower organizations to achieve measurable outcomes and deliver exceptional customer experiences in an ever-evolving digital landscape.
Qualifications
Must Have Skills/Project Experience/Certifications:
- 6-10 years of hands-on experience in a Data Engineering role with a strong focus on ETL development and data warehousing.
- Cloud Platform Expertise (At least one required):
- AWS: Deep hands-on experience with Glue, Redshift, S3, Athena, EMR, Lake Formation, and MSK/Kinesis.
- Azure: Deep hands-on experience with Azure Data Factory (ADF), ADLS Gen2, Event Hubs, Databricks (Delta Lake), and Synapse.
- GCP: Deep hands-on experience with GCS, BigQuery, Dataflow, Pub/Sub, and Cloud Composer (Airflow).
- Cloud Serverless & Event-Driven Data Architecture: Hands-on experience designing and deploying event-driven, serverless workflows using at least one of the following:-
- AWS: Lambda, Step Functions, and SQS/SNS.
- GCP: Cloud Functions, Cloud Run, GCP Workflows, and Pub/Sub.
- Azure: Azure Functions, Logic Apps, and Queue Storage/Event Grid.
- Agnostic Lakehouse Expertise: Expert-level use of Databricks and/or Snowflake.
- Medallion Architecture: Proven experience implementing Bronze, Silver, and Gold layers to manage data quality, ACID transactions, and lifecycle within a Data Lakehouse.
- Data Formats: Deep understanding of Parquet, JSON, CSV, Avro, and Delta/Iceberg trade-offs (performance, compaction, partitioning, and schema evolution).
- Data Governance & Security: Experience with lineage/catalog, access controls, encryption, and policy-driven sharing. Proficiency in implementing Fine-Grained Access Control (column/row-level security) and Data Masking for sensitive data.
- ETL & Migration:
- Strong background in Informatica (PowerCenter/IICS) for legacy and cloud-native workflows.
- Experience leading/supporting a Data Migration project from on-premises systems (Oracle, Teradata, SQL Server, Postgres, DB2, etc.) to a modern cloud environment.
- Programming & Scripting:
- SQL Mastery: Expert-level skills in Schema building, complex joins, window functions, and query tuning.
- Python: Strong proficiency for transformations (Pandas, PySpark), task automation, and API-led ingestion.
- Shell Scripting: Expert-level Linux/Unix Bash for environment setup, automated file transfers, and orchestrating job schedules.
Good to Have Skills/Project Experience/Certifications:
- AWS: Certified Data Engineer - Associate or Specialty.
- Azure: Azure Data Engineer Associate
- GCP: Professional Data Engineer.
- Agnostic: Snowflake Pro Core or Databricks Certified Data Engineer.
Education:
- BE/B.Tech/MCA/MSc Degree
Location:
· Bengaluru/Hyderabad/Pune/Chennai/