Principal – Data Engineer
Location: India, Remote
Experience: 8 Years
Algoworks
www.algoworks.com
About the company
Algoworks is an award-winning artificial intelligence, engineering services and experience transformation firm with offices across the United States, Europe, South America and India. We bring together a global team of engineers, architects, designers, researchers and operators united by rigor, accountability and a commitment to delivering measurable results.
For over 20 years, Algoworks has partnered with Fortune 500 organizations across the Americas, Europe and Asia to define, build and run technology that drives meaningful business outcomes. 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.
At Algoworks, growth is continuous and closely tied to impact. Teams collaborate across geographies and disciplines, strengthening outcomes through shared insight and collective expertise. The culture values transparency, open dialogue and an environment where every voice is heard and contribution is recognized.
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.
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Role overview
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.
Key responsibilities:
1.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.
2.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.
3.Reporting and data validation
- Support reporting platforms and troubleshoot data discrepancies impacting business users.
- Validate reporting accuracy and consistency across dashboards and operational reports.
- 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.
4.Monitoring and observability
- Implement and maintain monitoring for ETL pipelines, data freshness and reporting readiness.
- Develop dashboards for:
- Pipeline execution status
- Data completeness
- Data quality validation
- Data freshness monitoring
- Failed loads and exception tracking
- Establish alerting and operational support procedures for critical data failures.
5.Client and stakeholder communication
- 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.
- Lead technical review sessions and incident investigations.
- Provide regular updates on platform health, data quality metrics and support activities.
Required skills and qualification:
- 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).
- Stored Procedures, Views, Functions and Index optimization.
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.
- Production support and operational troubleshooting.
Leadership and communication requirements
- Experience leading data engineering teams.
- Strong client-facing communication skills.
- Ability to translate technical issues into business impacts.
- Experience coordinating efforts across business, reporting, engineering and operations teams.
- Strong documentation and analytical skills.
Must have skills:
- 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.
Nice to have skills:
- Experience supporting healthcare, public safety, or enterprise SaaS reporting platforms.
- Experience with Azure Fabric, Synapse, Databricks, or modern cloud data platforms.
- Exposure to data governance, master data management and reporting modernization initiatives.
Desired attributes:
- Strong ownership mindset with a focus on data reliability, platform stability and operational excellence.
- Excellent analytical and problem-solving skills with the ability to resolve complex data and reporting issues.
- Effective leadership and stakeholder management capabilities, with strong client-facing communication skills.
- Passion for mentoring teams, driving continuous improvement and delivering high-quality data solutions.
Interview process
2 rounds of discussion.