Job Summary
Drive complex data engineering and analytics solutions as a senior developer within a hybrid work model using Python Databricks SQL Databricks Workflows and PySpark to build scalable data pipelines and optimize data platforms. Collaborate with cross functional teams to deliver reliable insights improve system performance and support business decision making in a global enterprise environment.
Responsibilities
- Design and implement robust data pipelines using Python and PySpark to ingest transform and validate large scale structured and unstructured datasets in Databricks environments.
- Optimize Databricks SQL queries and data models to ensure efficient analytics performance reduced compute costs and fast delivery of insights to business stakeholders.
- Configure and manage Databricks Workflows to orchestrate complex end to end data processes including scheduling dependency handling and monitoring for reliability.
- Collaborate closely with data analysts and business partners to translate analytical requirements into maintainable technical solutions that directly support strategic objectives.
- Implement comprehensive data quality checks error handling and logging within Python and PySpark jobs to improve reliability observability and trust in delivered data products.
- Conduct performance tuning of PySpark jobs and Databricks SQL workloads to maximize resource utilization and minimize processing times across production and nonproduction environments.
- Apply secure coding and data handling practices within Databricks to protect sensitive information and comply with enterprise data governance policies and regulatory expectations.
- Review existing data workflows and pipelines to identify opportunities for simplification automation and standardization that reduce operational effort and improve scalability.
- Provide detailed technical documentation for data pipelines job configurations and workflow dependencies so that support teams and peers can easily maintain and enhance solutions.
- Support incident resolution and root cause analysis for data pipeline failures or performance degradations implementing preventive improvements for long term stability.
- Coordinate with platform and infrastructure teams to align Databricks cluster configurations libraries and integrations with evolving enterprise standards and best practices.
- Guide junior developers and peers through code reviews and knowledge sharing sessions focused on Python PySpark and Databricks usage improving overall team capability.
- Engage in continuous improvement activities by evaluating emerging Databricks features and Python ecosystem tools that can increase efficiency and expand analytics possibilities.
Qualifications
- Demonstrate strong proficiency in Python programming including modular design unit testing and effective use of data processing libraries in enterprise solutions.
- Exhibit advanced experience with PySpark for distributed data processing including working with large datasets optimizing transformations and managing performance.
- Show deep hands on expertise in Databricks SQL including writing complex queries building reusable views and tuning execution plans for analytic workloads.
- Apply practical experience configuring and operating Databricks Workflows for orchestration of production pipelines including job parameterization and monitoring.
- Display solid understanding of data warehousing concepts data modeling principles and relational database practices that underpin high quality analytics solutions.
- Demonstrate experience working in hybrid work models effectively collaborating through digital tools and coordinating onsite engagement as required by project work.
- Utilize strong problem solving skills and attention to detail to troubleshoot data and performance issues ensuring accurate and timely delivery of information to stakeholders.
Salary and Other Compensation:
The annual salary for this position is between $70-75K depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· 401(k) plan and contributions
· Long-term/Short-term Disability
· Paid Parental Leave
· Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable la
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
