Senior Data Engineer I
First seen by Alion on Aug 14, 2026.
Role :
Data Engineer plays a critical role in data and analytics life cycle and significantly contributes to production grade data and analytics solutions.
The role requires one to demonstrate Big Data, Engineering and Cloud expertise. This role mentors Data engineers.
It is an individual contributor role, expected to solve wide ranging business problems.
Experience : 8 - 10 years of relevant experience.
Education :
Bachelors degree in computer science, information technology or equivalent educational qualification.
Responsibilities :
- Design, build, and maintain robust ETL/ELT pipelines on cloud (Azure) or on-prem to collect, ingest and store large volumes of structured and unstructured data for batch/real time processing.
- Monitor, optimize, and troubleshoot data pipelines to ensure reliability, scalability, and performance.
- Ensure data processing, quality, security, and compliance guidelines, policies and standards are followed.
- Collaborate with multiple partners from Business, Technology, Operations and D&A capabilities (Data Governance, Data Quality, Data Modeling, Data Architecture, Data science, DevOps, BI & insights).
- Mentor Data Engineers.
- Independently lead design, solutioning & estimations.
Technical Skills :
- SQL, Python/Scala.
- NoSql and distributed databases (Hbase, Cosmos DB).
- ETL pipeline design and development; Solutioning and estimation.
- Big Data Frameworks : Apache Spark, Hadoop, Hive.
- Cloud platforms : Azure data factory, Eventhub, Azure functions, Synapse, Databricks.
- Datawarehouses, data marts, data lakes.
- Medallion architecture.
- Performance tuning, optimization, and data quality validation.
- Real-time and batch data processing, streaming pipelines with Spark.
- Communication skills, analytical skills, structured problem-solving skills, mentorship skills.
- Mentorship experience.
- Storytelling skills, Partner & Stakeholder engagement experience.
Good To Have :
- DevOps practices : Git, AzureDevops, CI/CD pipelines.
- Unix shell scripting, Kafka, MongoDB, Nifi.
- Exposure to Gen AI technology and tools.
- Banking Financial Services and Insurance domain knowledge.
Skills
Data Engineering, Big Data, ETL, Data Pipeline, Azure, SQL, Python, Scala, Medallion Architecture, Apache Spark