Data Engineer

Anteriad

Data Engineer at Anteriad optimizing data pipelines using Azure services. Partnering with stakeholders to create scalable data engineering solutions.

Posted 6/4/2026full-timeRemote • 🇮🇳 IndiaMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformMS SQL ServerPySparkPythonSparkSQLSSISVault

About the role

Key responsibilities & impact

Partner with technical and non-technical stakeholders to translate business requirements into scalable, reliable, and maintainable data engineering solutions.
Design, develop, and maintain data integration solutions using Microsoft SQL Server, Azure Data Factory, Azure Databricks, Microsoft Fabric, and related Azure services.
Build, manage, and optimize ETL/ELT pipelines using Azure Data Factory and Microsoft Fabric Pipelines, including pipeline orchestration, parameterization, scheduling, monitoring, and error handling.
Develop and maintain data transformation logic using Azure Databricks notebooks and Microsoft Fabric notebooks, with a focus on performance, scalability, reusability, and operational reliability.
Design and implement data ingestion, transformation, validation, and delivery processes across structured, semi-structured, and external data sources.
Develop and optimize data integration processes utilizing Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, Microsoft Fabric Lakehouses, Warehouses, Pipelines, and Notebooks.
Build and maintain SQL-based data models, stored procedures, views, automation scripts, and database objects to support operational and analytical workloads.
Support the modernization and migration of legacy data integration processes from SSIS and on-premises platforms to cloud-based Azure and Microsoft Fabric architectures.
Design and implement reusable pipeline patterns, data quality checks, validation controls, logging, alerting, and performance monitoring processes.
Support new client onboarding efforts by designing and implementing reliable data ingestion, transformation, reconciliation, and validation workflows.
Troubleshoot and resolve data pipeline, data quality, performance, and integration issues in collaboration with teams across Intelligence & Analytics.
Design, develop, and maintain datasets, semantic models, and data structures that support reporting, analytics, and visualization solutions across Power BI, Excel, Microsoft Fabric, and other business intelligence platforms.
Contribute to data engineering standards, documentation, best practices, and reusable frameworks that improve scalability, maintainability, and operational efficiency.
Research, evaluate, and recommend emerging technologies and platform capabilities that improve data architecture, automation, performance, and reliability.

Requirements

What you’ll need

3+ years of experience in data engineering, data integration, business intelligence engineering, or a related technical role.
3+ years of experience writing, optimizing, and troubleshooting SQL, including T-SQL, stored procedures, views, indexing strategies, and query performance tuning.
Hands-on experience designing, building, and supporting ETL/ELT pipelines using Azure Data Factory and/or Microsoft Fabric Pipelines.
Hands-on experience developing data processing and transformation logic using Azure Databricks notebooks, Microsoft Fabric notebooks, PySpark, Spark SQL, Python, or similar technologies.
Strong Microsoft SQL Server and relational database design principles skills.
Experience with Azure data platform services such as Azure Data Factory, Azure Databricks, Azure Storage Accounts, Azure Data Lake Storage, Azure Key Vault, and related cloud data services.
Strong knowledge and in depth work with Microsoft Fabric components such as Pipelines, Notebooks, Lakehouses, Warehouses, Dataflows, and semantic models.
Experience building reliable data ingestion and transformation processes from APIs, flat files, databases, web services, cloud storage, and other external data sources.
Hands on experience implementing data validation, reconciliation, monitoring, logging, and alerting processes for production data pipelines.
Experience supporting production data workloads, including troubleshooting failures, optimizing performance, and improving pipeline reliability.
Prior experience modernizing or migrating legacy ETL processes from SSIS, SQL Server, or on-premises environments to Azure or Microsoft Fabric is strongly preferred.
Bachelor’s degree in Computer Science, Information Technology, Data Analytics, a related field, or equivalent professional experience.
Power BI, semantic models, or other data visualization and analytics tools experience is a plus.
Experience with Customer Data Platforms, CDPs, database marketing, marketing analytics, or client data onboarding environments is a plus.
Working knowledge with AWS or Google Cloud Platform is a plus.
Strong analytical, problem-solving, and critical thinking skills.
Excellent verbal and written communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
Ability to work independently on moderately complex data engineering tasks while collaborating effectively in a team-oriented environment.

Benefits

Comp & perks

Work from home
Training & development with unlimited access to Percipio LMS
Mix of collaborative & independent work
Community outreach via Anteriad Cares - encouraging staff to take time to volunteer
Professional mentoring program - career guidance from leadership
Employee Resource Groups - collaborate with others that share your passions!

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata integrationETLELTSQLT-SQLAzure Data FactoryAzure Databricksdata transformationdata validation

Soft Skills

analytical skillsproblem-solvingcritical thinkingcommunication skillscollaborationindependence

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Information TechnologyBachelor's degree in Data Analytics