Data Engineers

Mandatory Skills required – Primary skill – Alteryx, Databricks and Azure Data Engineering. Secondary skill: Python

Shift Timings – UK Shift

Work Location - Bangalore – Should be willing to work from Office mandatorily.

Senior Manager Data Engineering - 13 to 15 years - 33165

Associate Architect Data Engineering - 5 to 7.5 yrs - 33167

Analyst Data Engineering - 2.5 to 4 yrs - 33170

Key Responsibilities:

∙Design, develop, and optimize scalable data pipelines and workflows using Azure Data Factory, Synapse Pipelines, and Microsoft Fabric.

∙Responsible for transforming and migrating existing Alteryx workflows into scalable Azure Databricks pipelines, ensuring optimized performance and maintainability.

∙Collaborate with data engineering and analytics teams to redesign Alteryx pipelines into Spark-based solutions on Azure Databricks, leveraging Delta Lake and Azure services for automation and efficiency.

∙Build and maintain ETL/ELT processes for ingesting structured and unstructured data from various sources.

∙Develop and manage data transformation logic using Databricks (PySpark/Spark SQL) and Python.

∙Collaborate with data analysts, architects, and business stakeholders to understand requirements and deliver high-quality data solutions.

∙Ensure data quality, integrity, and governance across the data lifecycle.

∙Implement monitoring and alerting for data pipelines to ensure reliability and performance.

∙Work with Azure Synapse Analytics to build data models and enable analytics and reporting.

∙Utilize SQL for querying and managing large datasets efficiently.

∙Participate in data architecture discussions and contribute to technical design decisions.

Required Skills and Qualifications:

∙3+ years of experience in data engineering or a related field.

∙Strong experience in Alteryx workflows and data preparation/ETL processes.

∙Strong proficiency in the Microsoft Azure data ecosystem including:

oAzure Data Factory (ADF)

oAzure Synapse Analytics

oMicrosoft Fabric

oAzure Databricks

∙Solid experience with Python and Apache Spark (including PySpark).

∙Advanced skills in SQL for data manipulation and transformation.

∙Experience in designing and implementing data lakes and data warehouses.

∙Familiarity with data governance, security, and compliance standards.

∙Strong analytical and problem-solving skills.

∙Excellent communication and collaboration abilities.

Preferred Qualifications:

∙Microsoft Azure certifications (e.g., Azure Data Engineer Associate).

∙Experience with DevOps tools and CI/CD practices in data workflows.

∙Knowledge of REST APIs and integration techniques.

∙Background in agile methodologies and working in cross-functional teams.