Big Data Technical Senior Associate Engineer

We are looking for a suitable candidate for the opening of the Senior/Associate Engineer role with good to have experience in the Banking and Financial Services domain with 4-6 years of relevant experience in Data Engineering / Big Data platforms. The candidate will work closely with Business, Risk, and Technology stakeholders to deliver scalable data products on Cloudera (CDH/CDP).

Key Roles & Responsibilities:

Must have / Primary Skills / Mandatory
- Hands-on experience building data pipelines on Hadoop/Spark ecosystem
- Strong Spark (Scala and/or PySpark), Hive/Impala SQL, and performance tuning
- Working knowledge of Kafka for streaming ingestion and NiFi (or StreamSets) for batch/near-real-time flows
- Experience with Cloudera Manager, YARN/Tez, HDFS, and job orchestration using Oozie/Airflow
- Good understanding of data warehousing concepts (dimensional modelling, partitioning, bucketing)
- Proficiency in Linux/Unix, Shell scripting, Git, and CI/CD (Jenkins/GitLab CI)
- Strong SQL and data modelling for BFSI use cases (lending,



liabilities, risk, regulatory reporting)
- Experience in writing technical design documents (HLD/LLD) and unit/integration testing
- Exposure to SDLC/Agile and working in onsiteoffshore model
- Location - Mumbai
- Develop robust Spark jobs (batch and streaming) with unit tests and observability
- Implement ingestion patterns (Kafka/NiFi), data quality checks, and job scheduling
- Analyze and tune SQL/Spark for large-scale datasets

Valuable to have / Secondary Skills / Desired
- Experience with Cloudera Data Platform (CDP) Private Cloud Base/Public Cloud
- Security and governance: Apache Ranger, Atlas; Kerberos; Sentry (legacy)
- Cloud data services – AWS (EMR, Glue, S3), Azure (HDInsight, Synapse, ADLS), or GCP (Dataproc, BigQuery)
- Databricks experience (Spark, Delta Lake) for select workloads
- Containerization and orchestration (Docker/Kubernetes) for micro-batch/ML workloads
- Python for

📌 Pyspark Developer (Mumbai)
🏢 PwC India
📍 Mumbai