Join our multinational corporation as a Developer focusing on PySpark and Python to design and implement scalable data solutions using Databricks platforms. This role demands expertise in managing workflows and SQL in Databricks to support data analytics initiatives in a hybrid work environment during daytime shifts with no travel requirements.
Responsibilities
- Develop test and deploy robust PySpark scripts and Python code to process large-scale datasets efficiently in conjunction with cloud-based data lake infrastructure.
- Design and implement Databricks Workflows to automate data pipeline orchestration ensuring timely data availability for analytics and reporting purposes.
- Create optimized SQL queries using Databricks SQL tools to extract transform and load data while maintaining accuracy and performance.
- Utilize Databricks CLI to manage workspace resources automate routine tasks and enhance productivity throughout the development lifecycle.
- Collaborate closely with data engineers and data scientists to integrate new data sources and refine existing pipelines for meeting evolving business requirements.
- Troubleshoot and resolve performance bottlenecks within data processing workflows by analyzing runtime metrics and applying optimization techniques.
- Apply data validation and quality assurance checks within pipelines to uphold data integrity and compliance with organizational standards.
- Participate in code reviews and contribute to maintaining coding standards documentation and best practices for sustainable development.
- Continuously monitor system activity and usage to proactively identify risks or opportunities for improvements in data infrastructure.
- Support cross-functional teams by delivering data-driven insights and technical expertise to accelerate the achievement of strategic goals.
- Adhere to internal security protocols and data privacy regulations while handling sensitive information throughout the data lifecycle.
- Engage in knowledge sharing and collaborative learning sessions to foster an innovative and inclusive team environment.
- Communicate progress and technical information effectively to stakeholders ensuring transparency and alignment with project timelines.
Qualifications
- Possess a minimum of two years hands-on experience developing data pipelines predominantly using PySpark and Python programming languages.
- Demonstrate proficiency with Databricks Workflows to construct and automate scalable ETL processes within cloud ecosystems.
- Show competence in writing complex queries using Databricks SQL to support advanced analytics use cases and data visualization efforts.
- Have practical skills in utilizing Databricks CLI for workplace configuration and administrative operations.
- Exhibit understanding of distributed computing frameworks data architecture principles and best practices in data engineering.
- Hold good-to-have knowledge of additional big data tools and frameworks facilitating seamless integration across platforms.
- Adapt comfortably to a hybrid work model blending onsite collaboration and remote productivity with self-driven accountability.
- Operate primarily in daytime shift hours following company schedule demands without requirements for business travel.
- Communicate fluently in English to interact with global team members and stakeholders effectively.
Certifications Required Databricks Certified Associate Developer for Apache Spark or equivalent certification preferred.
📌 Databricks+spark (Indore)
🏢 Cognizant
📍 Indore
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