Experience: 3–5 Years (Maximum 5 Years)

Relevant Experience: 3+ Years

Locations: Bangalore – 6 positions | Hyderabad – 2 positions

Work Mode: WFO – 5 Days/Week

CTC: ₹20–22 LPA

Role Overview

We are looking for Data Engineers to join a Datastore Migration Factory team responsible for end-to-end migration from an on-premise Data Lake to an AWS-hosted LakeHouse .

The role involves pipeline migration, SQL/Spark code conversion, data migration, data reconciliation, data modelling, and stakeholder coordination to ensure migrated data and consumption patterns meet business requirements.

Key Responsibilities

1. Pipeline Migration

- Refactor and migrate extraction logic and job scheduling from legacy frameworks to the new LakeHouse environment.
- Execute physical migration of datasets while maintaining data integrity.
- Coordinate with data owners for technical hand-off and sign-off.

2. Consumption Pattern Migration

- Convert and optimize legacy SQL and Spark consumption patterns for Snowflake and Apache Iceberg .
- Analyze usage patterns and deliver required data products.
- Coordinate with stakeholders for hand-off and sign-off.

3. Data Reconciliation & Quality

- Perform rigorous data validation and reconciliation.
- Use reconciliation frameworks to establish functional equivalence between migrated and production data.




- Identify and troubleshoot data discrepancies.

4. Engineering & Collaboration

- Work with internal data management platform teams.
- Learn and adapt to new workflows, tools, and language constructs.
- Follow SDLC and CI/CD best practices.
- Support Kubernetes (K8s) deployments.

Mandatory Technical Skills

- ? 3–5 years hands-on Data Engineering experience
- ? SQL
- ? Data Modelling
- ? Pipeline/Data Migration
- ? Python OR Java
- ? Robust SQL troubleshooting
- ? SDLC & CI/CD
- ? Kubernetes/K8s deployment experience
- Temporal Data Modelling – SCD Type 2
- Schema Evolution & Schema Management
- Data Partitioning & Clustering
- Normalization vs. Denormalization
- Natural vs. Surrogate Keys

Technical Stack Extraction & Processing

- Kafka
- ANSI SQL
- FTP
- Apache Spark

Data Formats

- JSON
- Avro
- Parquet

Platforms

- Hadoop / HDFS / Hive
- Snowflake
- Apache Iceberg
- Sybase IQ

Candidate Profile

Candidates should demonstrate

- Strong analytical and troubleshooting ability.
- Ownership and delivery focus.
- Clear communication and stakeholder management.
- Ability to collaborate with global and cross-functional teams.
- Ability to identify risks and resolve issues constructively.
- Willingness to learn new technologies and workflows.

📌 Data Engineer – AWS | Snowflake | Spark | Data Migration (Bengaluru)
🏢 Asian Hires
📍 Bengaluru