About Company FiftyFive is a global software development and technology consulting company, delivering full-cycle digital solutions across industries and geographies. We help businesses across the USA, UK, Australia, MENA, and the Nordics accelerate innovation and drive digital transformation. Our offerings span: - Custom Software & MVP Development - Web & Mobile App Development - Cloud Engineering (AWS, Azure, GCP) - Embedded Software & IoT Solutions - UI/UX and 3D Design - Software Testing & QA We specialize in cutting-edge technologies including: - AI/ML, Data Engineering, and Blockchain - Cybersecurity & DevOps - Robotic Process Automation - Sustainability-Focused Digital Initiatives We also support: - Legacy Modernization - IT Consulting & System Integrations - ERP/CRM Implementation (SAP, Microsoft Dynamics, Salesforce) - Power BI, OpenAI/ChatGPT, and other third-party integrations Through flexible remote team extension services, we help businesses build scalable and cost-effective engineering teams that move fast. Our domain expertise spans finance, healthcare, manufacturing, energy, logistics, retail, e-commerce, telecommunications, and more, empowering clients to solve complex challenges, optimize operations, and drive sustainable growth.

Website- https://www.fiftyfivetech.io/

Location: Gurgaon / Indore / Jaipur (Hybrid)

Experience: 5–9 Years

• Good to Have

Experience with Microsoft Purview or Informatica.

Exposure to Power BI or other reporting/visualization tools.

Knowledge of Medallion Architecture and Lakehouse concepts.

Experience supporting AI/ML data engineering workflows.

Familiarity with cloud security and governance best practices.

Key Responsibilities

• Design, develop, and maintain scalable end-to-end data pipelines using Python, SQL, and Azure services.

• Build and optimize ETL/ELT workflows for large-scale enterprise data processing.

• Work extensively with Azure Data Factory (ADF), Azure Databricks, Azure Data Lake, and Azure Synapse Analytics.

• Develop scalable data ingestion frameworks for APIs, relational databases, flat files, and cloud data sources.

• Perform data transformation, cleansing, validation, and performance optimization using PySpark and Pandas.

• Implement modern data lake and lakehouse architectures including Medallion Architecture.

• Write optimized SQL queries, stored procedures, and data validation logic.

• Monitor, troubleshoot, and improve pipeline performance and data quality.

• Collaborate with Data Analysts, BI Developers, Architects, and Business Stakeholders.

• Implement CI/CD pipelines, deployment automation, and version control best practices.

• Maintain technical documentation, operational runbooks, and data workflow standards.

• Support cloud migration and enterprise data modernization initiatives.