SSIS Data engineer

EPAM Systems Inc; Hyderabad, Pune District, Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

EPAM Systems Inc. is seeking a data engineer to clean and validate data, join datasets from multiple sources, and apply business logic such as currency conversion and categorization.

The role involves aggregating data, writing processed information into data warehouses or lakes, and optimizing batch loads for analytics readiness. You will manage data retention and ensure consistency and standardization across analytics-ready datasets.

Qualifications

• Experience cleaning and validating data: removing duplicates, fixing formats, handling nulls.
• Knowledge of joining and merging datasets from multiple sources.
• Ability to apply business logic such as currency conversion and categorization.

Responsibilities

• Cleaning and validating data (removing duplicates, fixing formats, handling nulls).
• Joining and merging datasets from different sources.
• Applying business logic (e.g., currency conversion, categorization).
• Aggregating and summarizing data.
• Writing processed data into the target system (data warehouse, data lake, BI system).
• Optimizing load performance (batch loading, parallel processing, partitioning).
• Managing data retention and historical records.
• Ensuring data is consistent, standardized, and analytics-ready.

Skills

SQL/T-SQL

Performance tuning

SQL Server

Data pipelines

Data modeling

Batch scheduling

Source control

Tools

Control-M

Subversion

GitHub

Job description

Key Responsibilities

• Cleaning and validating data (removing duplicates, fixing formats, handling nulls).


• Joining and merging datasets from different sources.


• Applying business logic (e.g., currency conversion, categorization).


• Aggregating and summarizing data.


• Writing processed data into the target system (data warehouse, data lake, BI system).


• Optimizing load performance (batch loading, parallel processing, partitioning).


• Managing data retention and historical records.


• Ensuring data is consistent, standardized, and analytics-ready.

Diagnosing issues and applying technical changes to remediate

Essential Skills

• advanced proficiency


• SQL/T-SQL, Performance monitor and tuning


• Databases: SQL Server


• Data pipelines, lineage


• Data modelling:star or snowflake schemas


• Batch scheduling, such as Control-M


• Source control, such as Subversion and GitHub