Sr.Data Engineer(IDMC/IICS+Snowflake)

Excelencia; Pune District; On-site; INR 1,200,000 - 2,200,000; Full time

Benefits offered by this job

Cross-functional teams

Job summary

Excelencia is seeking an experienced Data Engineering professional to develop and optimize end-to-end data pipelines for supply chain datasets. You will work across ETL/ELT processes, design data models, and ensure data quality in a cloud-based BI architecture.

The role requires deep expertise in SQL, big data tools, and data governance, with exposure to SAP/Oracle ecosystems and cross-functional agile collaboration.

Qualifications

• 10+ years of experience in BI/ETL and data warehousing.
• Proficient in SQL and data modeling for supply chain datasets.
• Hands-on with Data Integration tools and cloud data platforms.
• Experience building scalable, resilient data pipelines.
• Familiar with AI/ML frameworks is a plus.

Responsibilities

• Develop, maintain, and enhance data pipelines (ETL/ELT).
• Optimize complex SQL queries for performance.
• Design semantic data models and KPI-centric data marts.
• Lead data sourcing, testing, and deployment in BI architecture.
• Ensure data security and governance across pipelines.
• Collaborate with cross-functional teams in agile sprints.

Skills

ETL pipelines

SQL optimization

Data modeling

Big data

Scala

Python

Java

C++

PowerCenter

IDMC/IICS

Snowflake

Databricks

Hadoop

Kafka

Spark

SQL databases

NoSQL databases

Data governance

Purview

Agile

Education

Bachelor's degree in CS/IT

Tools

Oracle

MS Synapse

Redshift

BigQuery

Job description

Location:

Pune / Chennai / Hyderabad

Experience:

10+ Years

Required Skills:

• Development, maintenance, and enhancement of Data Pipelines (ETL/ELT) and processes with thorough knowledge of star/snowflake schemas
• Developing complex SQL queries and SQL optimization
• Hands on experience in PowerCenter/IDMC/IICS.
• Development experience must be full Life Cycle experience including business requirements gathering, data sourcing, testing/data reconciliation, and deployment within Business Intelligence/Data Warehousing Architecture.
• Designing and implementing data security
• Monitoring and optimizing data storage and data processing
• Use of Object function/object-oriented scripting languages including Scala, C++, Java and Python
• Cloud data warehouse and data lake platforms (e.g., Snowflake, Databricks, Redshift, BigQuery, MS Synapse, MS ADLS, Apache Haddop, etc.)
• Developing data services that are fit for purpose, resilient, scalable, and future proof, to meet user needs
• Advanced SQL knowledge and experience working with relational databases and working familiarity with various databases.
• Demonstrated understanding and experience using software and tools including ETL, relational SQL and NoSQL databases, big data tools like Kafka, Spark, and Hadoop
• Experience building and optimizing 'big data' data pipelines, architecture, and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Experience and knowledge of project management best practices and agile software development methodologies
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• Understanding of data science concepts
• Familiarity with AI/ML frameworks and libraries

Additional Skills: Good to Have

Experience in Supply Chain and Manufacturing Domains - understand the data, the use cases, and the value it drives rather than just the code"

• Inventory and warehouse management data
• Demand planning and forecasting
• Production orders, BOMs, routings
• Quality systems (defects, CAPA, nonconformance)

Data Integration Across Various Source Systems - comfortable with messy enterprise ecosystems and excels in data transformation and harmonization across systems"

• SAP Experience (high priority)
• SAP pipeline integration (high priority)
• Oracle, Syteline, MAAPS, AS400

Focus on Data Modeling and Analytics Engineering

- "candidate can explain how they modeled a supply chain dataset (orders, shipments, inventory) into a consumable reporting layer."

• Semantic / business layer modeling background
• Fact / dimension modeling to KPI's (not just tables)
• Data Marts and Info Mart creation and maintenance
• Ability to translate business processes and KPIs into data structures
• Emphasis on data quality, data governance, and metadata / catalog integration (Purview, Collibra, etc.)