• Pune
• Cummins India

**DESCRIPTION**


**Although the role category specified in the GPP is Remote, the requirement is for Hyrid.**


**Key Responsibilities** :


+ **Design&Development** : Design and automate the deployment of distributed systems for ingesting and transforming data from various types of sources (relational, event-based, unstructured).

+ **Data Quality&Integrity** : Design and implement frameworks for continuously monitoring and troubleshooting data quality and integrity issues.

+ **Data Governance** : Implement data governance processes, ensuring effective management of metadata, access, and retention for both internal and external users.

+ **ETL Pipelines** : Design and provide guidance on building reliable, efficient, and scalable data pipelines that integrate data from diverse sources using ETL/ELT tools or custom scripting.

+ **Database Optimization** : Develop and implement physical data models and optimize database performance using efficient indexing and table relationships.

+ **Cloud Data Solutions** : Create and manage large-scale data storage and processing solutions using cloud-based platforms like Azure Databricks, Data Lakes, Hadoop, and NoSQL databases (e.g., Cassandra, MongoDB).

+ **Automation&Productivity** : Leverage modern tools and techniques to automate repeatable data preparation and integration tasks, minimizing manual efforts and error-prone processes.

+ **Agile Methodologies** : Participate in agile development methodologies such as DevOps, Scrum, and Kanban to ensure timely delivery of critical analytics initiatives.

+ **Mentorship&Collaboration** : Mentor junior developers, collaborate with cross-functional teams, and contribute to the overall success of the data platform.


**RESPONSIBILITIES**


**Qualifications** **:**


**Knowledge/Skills** :


+ Proven track record in developing efficient data pipelines and mentoring junior developers.

+ Hands-on experience with Spark (Scala/PySpark), SQL, and Spark Streaming.

+ Proficient in troubleshooting and optimizing batch/streaming data pipeline issues.

+ Expertise in Azure Cloud Services (Azure Databricks, ADLS, EventHub, EventGrid, etc.).

+ Strong understanding of data models (SQL/NoSQL), including Delta Lake or Lakehouse.

+ Experience with CI/CD tools for automating deployments.

+ Knowledge of big data storage strategies, performance optimization, and database indexing.

+ Familiarity with Agile software development methodologies.


**Nice-to-Have** :


+ Understanding of the machine learning lifecycle and experience integrating ML models into data pipelines.

+ Exposure to open-source big data technologies and IoT.

+ Familiarity with building analytical solutions in cloud environments.

+ Experience in large file movement and data extraction tools.


**Education&Certifications** **:**


+ A degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent relevant experience is required.

+ Additional certifications in Azure, Spark, or cloud-based data engineering solutions are a plus.


**Competencies** **:**


+ **System Requirements Engineering** : Ability to translate stakeholder needs into verifiable system requirements, ensuring alignment with project goals.

+ **Collaboration** : Strong ability to build partnerships and work effectively within cross-functional teams to achieve shared objectives.

+ **Effective Communication** : Skilled in delivering clear communications to diverse audiences, both technical and non-technical.

+ **Customer Focus** : Dedicated to building strong customer relationships and delivering solutions that meet their needs.

+ **Problem Solving** : Proficient in using systematic analysis and industry-standard methodologies to solve complex technical challenges.

+ **Data Quality** : Knowledgeable in identifying, understanding, and correcting data quality issues across operational processes.

+ **Solution Documentation&Testing** : Thorough in documenting solutions and validating them through structured testing practices to ensure they meet business requirements.

+ **Decision Making** : Able to make timely, data-driven decisions that maintain project momentum.


**QUALIFICATIONS**


**Skills&Experience** **:**


+ **Experience** :

+ 6-8 years of hands-on experience in data engineering, with a focus on building data pipelines, and working with cloud-based data solutions (preferably Azure Databricks).

+ Advanced knowledge in Spark (Scala/PySpark), SQL, and cloud platforms like Azure.

+ Familiarity with the design, development, and maintenance of large-scale data storage solutions (Hadoop, NoSQL databases, Data Lakes).

+ Experience in mentoring junior developers and working in Agile development teams.

+ **Technical Skills** :

+ Advanced proficiency in SQL and Spark.

+ Expertise in data pipeline design and automation.

+ Knowledge of cloud data services (Azure Databricks, ADLS, EventHub, EventGrid).

+ Experience with CI/CD tools for pipeline deployment automation.

+ Familiarity with big data tools like Hive, Kafka, Hbase, and the use of Delta Lake.

+ Experience in building and optimizing ETL/ELT pipelines.


**Work Schedule** **:**


This role requires collaboration with stakeholders in the US, with an expected overlap of 2-3 hours during EST working hours on an as-needed basis.


**Job** Systems/Information Technology

**Organization** Cummins Inc.

**Role Category** Remote

**Job Type** Exempt - Experienced

**ReqID** 2412312

**Relocation Package** No