About Trantor:

Trantor is a technology services company focused on outsourced product development and digital re-engineering. Leveraging our CaptiveCoE™ engagement model, we operate as a seamless extension of our client’s teams to provide rapid scalability with predictable budgets. Founded in 2012, Trantor has worked with customers across Tech, FinTech, Media & Cybersecurity industries. We have centers in the US, India, Canada, and Costa Rica. We are consistently rated as the #1 employer in the region with the ability to attract and retain technical talent. Our commitment to excellence and impactful results has translated to long-term relationships and value for our clients and solution partners.                                                                                                                                       

Job Description:

We are seeking a data engineer to design, implement, and optimize cloud-based data pipelines using Microsoft Azure services, including ADF, Synapse, and ADLS.

Job Role & Responsibilities

• Develop and maintain ETL/ELT pipelines using Azure Data Factory to ingest, transform, and load data from diverse sources (databases, APIs, flat files).
• Design and manage data storage solutions using Azure Blob Storage and ADLS Gen2, ensuring proper partitioning, compression, and lifecycle policies for performance and cost efficiency.
• Build and optimize data models and analytical queries in Azure Synapse Analytics, collaborating with data architects to support reporting and BI needs.
• Ensure data quality, consistency, and reliability through validation, reconciliation, auditing, and monitoring frameworks.
• Collaborate with data architects, BI developers, and business teams to define architecture, integration patterns, and performance tuning strategies.
• Implement data security best practices, including encryption, access control, and role-based access management (RBAC).
• Create and maintain documentation of data workflows, pipelines, and architecture to support knowledge transfer, compliance, and audits.

Skills Required

• 5+ years of hands-on experience in data engineering with a strong focus on Azure Data Factory, Azure Synapse Analytics, and ADLS Gen2.
• Strong expertise in SQL, performance tuning, and query optimization for large-scale datasets.
• Experience designing and managing data pipelines for structured and semi-structured data (CSV, JSON, Parquet, etc.).
• Proficiency in data modeling (star schema, snowflake, normalized models) for analytics and BI use cases.
• Practical knowledge of data validation, reconciliation frameworks, and monitoring pipelines to ensure data reliability.
• Solid understanding of data security best practices (encryption, RBAC, compliance standards like GDPR).
• Strong collaboration skills, with the ability to work closely with architects, BI teams, and business stakeholders.
• Excellent skills in documentation and process standardization.

Good-to-Have Skills

• Experience with Python/Scala scripting for automation of ETL and data quality checks.
• Exposure to Power BI or other BI tools (Tableau, Qlik) for understanding downstream analytics requirements.
• Familiarity with CI/CD pipelines for data projects using Azure DevOps or Git-based workflows.
• Knowledge of big data frameworks (Databricks, Spark) for large-scale transformations.
• Hands-on experience with metadata management, data lineage tools, or governance frameworks.
• Exposure to cloud cost optimization practices in Azure environments.
• Understanding of API-based ingestion and event-driven architectures (Kafka, Event Hub)