Role: Data Engineer II (SDE-2)

Experience: 3–5 Years

Joining: IMMEDIATE

About the Role

We are looking for a Data Engineer II (SDE-2) to join our Data Platform team and build scalable, high-performance data infrastructure powering real-time analytics and business-critical applications. In this role, you will design and develop modern Lakehouse architectures , build low-latency data pipelines , and optimize distributed data processing systems on AWS . You will work closely with Product, Engineering, and Analytics teams to deliver reliable, scalable, and efficient data solutions.

Key Responsibilities

- Design, build, and maintain scalable batch and real-time data pipelines.
- Develop and manage Change Data Capture (CDC) pipelines using technologies like Debezium, PeerDB , or similar.
- Design and optimize Lakehouse architectures using Apache Iceberg, Delta Lake, or Apache Hudi .
- Build robust ETL/ELT pipelines using PySpark and Apache Flink .
- Manage and optimize data infrastructure on AWS (S3, EMR, EKS, MSK) .
- Tune distributed query engines such as Trino or ClickHouse for high-performance analytics.
- Design dimensional data models including Fact Tables, Dimension Tables, SCDs, and OBTs .
- Automate deployments and infrastructure using GitLab/GitHub Actions and Terraform .
- Drive technical design discussions, architecture reviews, and documentation.
- Collaborate with Product and Business teams to deliver data solutions that enable analytics and decision-making.

Required Skills





- 3–5 years of experience in Data Engineering building scalable data platforms.
- Robust programming skills in Python (PySpark) and SQL .
- Hands-on experience with Apache Spark and distributed data processing.
- Experience building batch and streaming data pipelines.
- Strong knowledge of AWS services such as S3, EMR, EKS, and MSK .
- Experience with workflow orchestration tools like Airflow or Temporal .
- Understanding of contemporary Lakehouse technologies ( Iceberg, Delta Lake, or Hudi ).
- Experience with distributed query engines such as Trino or ClickHouse .
- Good understanding of data modeling concepts including Fact/Dimension modeling and Slowly Changing Dimensions (SCDs) .
- Solid problem-solving skills and ability to work in a fast-paced product engineering environment.

Good to Have

- Experience with Kafka , Debezium , or PeerDB .
- Exposure to Terraform , GitLab CI/CD , or GitHub Actions .
- Programming experience in Go, Java, or Scala .
- Experience using AI-assisted development tools such as GitHub Copilot, Claude, or Codex .

Tech Stack

- Languages: Python, SQL (Go/Java/Scala – good to have)
- Data Processing: PySpark, Apache Flink
- Streaming & CDC: Kafka (MSK), Debezium, PeerDB
- Storage: Apache Iceberg , Delta Lake , Apache Hudi
- Cloud: AWS (S3, EMR, EKS, MSK)
- Query Engines: Trino, ClickHouse
- Orchestration: Airflow, Temporal
- DevOps: GitLab CI/CD, GitHub Actions, Terraform
- BI & Visualization: Metabase, Superset, Tableau, Power BI

📌 AWS Data Engineer - SDE 2 (Bengaluru)
🏢 Recro
📍 Bengaluru