Senior Data Engineer

ISHIR

IndiaremotePosted 12 days ago

Skill Required

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Key highlights

Requires 6–8 years of professional experience in Data Engineering.
Requires strong hands-on expertise with Microsoft SQL Server.
Requires advanced SQL skills, including query optimization and performance tuning.
Must overlap with US Pacific Time for client meetings.
Experience creating Power BI data models is preferred.
Experience working with legacy systems and highly inconsistent or fragmented data is preferred.

Role overview

We are seeking a Senior Data Engineer with 6–8 years of experience to build and maintain reliable data pipelines and a shared data foundation across multiple source systems. The role involves managing complex, inconsistent, and legacy data environments while ensuring robust ETL/ELT pipeline integrity and high data quality. Success in this position requires strong analytical and problem-solving abilities, independence, and the capacity to communicate data-related issues clearly to both technical and business stakeholders, with availability overlapping with US Pacific Time for client meetings.

Responsibilities

Extract and integrate data from SQL databases, spreadsheets, ERP report exports, and other source systems.
Clean, standardize, match, and reconcile data across multiple systems.
Perform data quality checks, deduplication, validation, and reconciliation.
Design, develop, and maintain reliable ETL/ELT pipelines and data loads.
Build standardized data models that integrate data from multiple source systems.
Develop and maintain operational and reporting data models.
Create and maintain a data dictionary with agreed definitions, mappings, and business rules.
Develop and maintain integration processes for systems with limited or no APIs using report exports, flat files, or other appropriate methods.
Write and optimize complex SQL queries, stored procedures, and database processes.
Perform SQL Server performance tuning and troubleshoot database-related issues.
Implement appropriate data masking, access controls, and least-privilege practices.
Investigate data discrepancies and identify root causes.
Collaborate with BI analysts and application developers to support reporting and application requirements.
Document data processes, mappings, and technical solutions.
Communicate technical findings and data issues clearly to stakeholders.
Strong ownership and attention to detail.
A structured approach to solving complex data problems.
Ability to work effectively with messy and incomplete data.
Ability to translate technical data issues into clear business explanations.
A proactive approach to identifying data-quality and integration challenges.
Ability to collaborate effectively with technical and non-technical stakeholders.

Requirements

6–8 years of professional experience in Data Engineering.
Strong hands-on expertise with Microsoft SQL Server.
Advanced SQL skills, including query optimization and performance tuning.
Strong experience with ETL/ELT development and data integration.
SSIS
Azure Data Factory
Python
Strong understanding of data modeling for operational and reporting environments.
Data cleansing
Data matching
Deduplication
Data validation
Data reconciliation
Experience integrating data from ERP systems through reports, exports, flat files, or similar methods.
Experience with data masking, security, and access controls.
Strong analytical, troubleshooting, and problem-solving skills.
Ability to work independently and manage data engineering tasks with minimal supervision.
Strong written and verbal communication skills.
Strong ownership and attention to detail.
A structured approach to solving complex data problems.
Ability to work effectively with messy and incomplete data.
Ability to translate technical data issues into clear business explanations.
A proactive approach to identifying data-quality and integration challenges.
Ability to collaborate effectively with technical and non-technical stakeholders.

Nice to have

Experience creating Power BI data models.
Experience working with inventory, procurement, supply-chain, or ERP data.
Experience in agriculture, food, manufacturing, or related industries.
Experience working directly with client-side IT teams and business stakeholders.
Experience working with legacy systems and highly inconsistent or fragmented data.