Principal Data Engineer - Fully Remote

Principal Data Engineer Location: India, Remote

Experience: 8 Years

Algoworks is an award-winning artificial intelligence, engineering services and experience transformation firm with offices across the United States, Europe, South America and India. Our work combines human-centered design, engineering excellence and AI-powered capabilities to solve complex challenges with clarity and precision. Innovation, particularly in the responsible application of AI, is embedded in how teams approach problem-solving and continuous improvement.

Through collaboration, accountability and a focus on results, Algoworks operates at the intersection of technology and people, building not only advanced systems but strong global teams that elevate performance and create lasting impact.

Follow the video below to know about us! We are seeking an experienced Lead Data Platform Engineer to lead the support, stabilization and enhancement of our enterprise data platform. This role will be responsible for troubleshooting complex ETL and Data Warehouse issues, improving data quality and reporting reliability, mentoring data engineers and serving as the primary technical contact for data-related client discussions.

The ideal candidate will possess deep expertise in ETL pipelines, SQL, data warehousing, reporting systems and root-cause analysis, while also demonstrating strong leadership and stakeholder communication skills.

Data platform leadership

Lead a team of data engineers supporting enterprise data integration and reporting platforms.

Establish best practices for ETL development, monitoring, testing, deployment and support.

Drive continuous improvements in data quality, platform reliability and operational efficiency.

Provide technical leadership for data architecture, ingestion frameworks and reporting solutions.

ETL and data warehouse support

Investigate and resolve complex ETL failures, data load issues and reporting discrepancies.

Troubleshoot data flow issues across source systems, staging layers data warehouse and reporting environments.

Perform root-cause analysis of data quality, completeness and reconciliation issues.

Analyze source-to-target mappings and validate data transformations.

Optimize ETL processes for performance, scalability and maintainability.

Support data warehouse operations, including dimensional models, fact tables and reporting datasets.

Reporting and data validation

Support reporting platforms and troubleshoot data discrepancies impacting business users.

Investigate missing, delayed, duplicated, or incorrect data in reports and downstream systems.

Partner with business stakeholders to understand reporting requirements and data issues.

Define and implement data quality controls and validation frameworks.

Monitoring and observability

Implement and maintain monitoring for ETL pipelines, data freshness and reporting readiness.

Data completeness

Data quality validation

Data freshness monitoring

Establish alerting and operational support procedures for critical data failures.

Serve as a technical point of contact for data platform and reporting discussions.

Communicate findings, risks, root causes and remediation plans to clients and stakeholders.

Provide regular updates on platform health, data quality metrics and support activities.

Bachelor's degree in computer science, Information Technology, Business Administration, or a related field.

10+ years of experience in Data Engineering, ETL, or Data Warehouse environments.3+ years leading data engineering teams.

Data engineering

Strong ETL/ELT development experience.

Experience in C#, SSIS is must.

Data warehouse architecture and design.

Data integration and transformation frameworks.

Experience supporting large-scale enterprise reporting environments.

Database

Advanced SQL Server expertise.

Query tuning and performance optimization.

Data modeling (star schema, dimensional modeling).

Cloud and modern data platforms

Azure Data Factory, Fabric, Synapse, Databricks, or similar platforms.

Experience with modern data lake and warehouse architectures.

Data orchestration and scheduling frameworks.

Monitoring and support

ETL monitoring and observability.

Data quality frameworks and validation processes.

Incident management and root-cause analysis.

Experience leading data engineering teams.

Experience coordinating efforts across business, reporting, engineering and operations teams.

Strong experience in .NET/C# development, Microsoft SSIS, ETL/ELT pipelines and enterprise data integration solutions.

Expertise in SQL Server, data warehousing, data modeling, query optimization and performance tuning.

Hands-on experience with data troubleshooting, root-cause analysis, data quality validation and production support in large-scale environments

Proven experience leading data engineering teams and working with business stakeholders, reporting teams and clients.

Experience supporting healthcare, public safety, or enterprise SaaS reporting .