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Azure data bricks +Pyspark

00069371093

Skill: Azure Databricks

Experience: 6 to 12 years

Location: AIA Bhubaneshwar

Job Summary

The Sr Developer will design and optimize scalable data solutions using Databricks SQL Databricks Workflows and PySpark for a global enterprise operating in a hybrid work model. The role focuses on building reliable analytics pipelines improving data quality and enabling data driven decisions that support business growth and positive impact on customers and communities.


Responsibilities

  • Develop and maintain robust data pipelines using Databricks Workflows and PySpark to deliver reliable and timely data assets for analytics consumers within the organization.
  • Design and optimize complex Databricks SQL queries that transform large scale datasets into efficient reusable views and tables aligned to business reporting needs.
  • Implement modular PySpark code structures that promote reusability testability and performance while adhering to the organizations coding standards and guidelines.
  • Build and schedule Databricks Workflows that orchestrate end to end data processing tasks including ingestion transformation validation and publishing to downstream systems.
  • Optimize cluster configurations and job parameters in Databricks to balance performance cost efficiency and stability for critical production workloads.
  • Develop robust data quality checks and validation routines in PySpark and Databricks SQL that detect anomalies and ensure high confidence in analytical outputs.
  • Collaborate with data analysts and product stakeholders to understand functional requirements and translate them into scalable Databricks based technical solutions.
  • Document data models transformation logic workflow dependencies and operational procedures in a clear and structured manner to support maintainability and knowledge sharing.
  • Troubleshoot production incidents by analyzing logs investigating data issues and implementing sustainable fixes that enhance reliability of the data platform.
  • Contribute to continuous improvement initiatives by identifying opportunities to simplify logic reduce processing time and eliminate manual interventions across workflows.
  • Mentor less experienced developers by reviewing code sharing best practices in PySpark and Databricks usage and encouraging high quality engineering habits.
  • Partner with enterprise technology teams to ensure that data solutions align with security governance and compliance expectations thereby protecting organizational and customer data.
  • Drive innovation by exploring advanced features of the Databricks platform and applying them to create impactful solutions that enable better decisions and positive outcomes for society.


Qualifications

  • Possess six to ten years of professional experience in data engineering or related development roles with a strong focus on building production grade data solutions.
  • Demonstrate advanced proficiency in Databricks SQL including window functions complex joins performance tuning and the creation of reusable analytical datasets.
  • Exhibit deep hands on experience with PySpark for developing scalable batch and streaming data pipelines that operate on large and diverse data sources.
  • Show proven capability in configuring and managing Databricks Workflows for orchestrating multi step jobs handling dependencies and monitoring executions in production.
  • Bring solid understanding of data warehousing concepts dimensional modeling and best practices for structuring analytics ready data in lakehouse environments.
  • Apply strong skills in debugging unit testing and automated validation to ensure that data pipelines are resilient maintainable and easy to enhance.
  • Demonstrate effective communication abilities to collaborate with cross functional teams in a hybrid work model and to explain technical concepts in accessible language.
  • Display familiarity with version control practices and collaborative development workflows that support code review branching strategies and continuous integration.
  • Value inclusive and ethical data practices ensuring that data solutions support responsible decision making and contribute to positive outcomes for customers and communities.


Certifications Required


关于高知特 (Cognizant)
高知特(Cognizant)(纳斯达克代码:CTSH)作为一家AI Builder和相关技术服务提供商,致力于通过打造全栈AI解决方案,帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长,将企业独特的业务场景融入科技系统,赋能组织释放人才潜能,推动切实成果,并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情,敬请访问 cognizant.ai 或关注@cognizant。

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