IN_Senior Associate_Databricks- Data and Analytics_Advisory_Pan India at pwc

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

06 Jun, 26

Salary

0.0

Posted On

08 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Data Pipelines, Data Architecture, Data Modeling, Delta Lake, Unity Catalog, ETL, Apache Spark, Databricks SQL, AI/ML, NLP, Generative AI, Data Engineering, Data Integration, Data Security, Data Governance

Industry

Professional Services

Description

Line of Service Advisory Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate Job Description & Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us. At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. Responsibilities: · Design, develop, and implement end-to-end data solutions using the Databricks Lakehouse platform architecture. · Collaborate closely with data architects to capture data requirements and translate them into scalable and efficient technical solutions. · Architect and optimize data pipelines, data lakes, and data models to support various business needs, leveraging Delta Lake for reliable data storage. · Implement data security, governance, and cataloging measures using Unity Catalog within Databricks data solutions. · Develop robust ETL processes using Apache Spark and Databricks functionalities, integrating Databricks SQL for data warehousing purposes. · Utilize Databricks ML to design and deploy AI/ML models tailored for specific business requirements. · Integrate data solutions seamlessly with existing systems by collaborating with cross-functional teams. · Diagnose and resolve data-related issues, ensuring optimal performance of data solutions. Mandatory skill sets: AI/ML, NLP, and Generative AI models, Preferred skill sets: Azure, Google Cloud Years of experience required: 3-5 Years Education qualification: Advanced degree (Master’s or Ph.D.) in Computer Science, Artificial Intelligence, Data Science, or related discipline. Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master Degree, Bachelor Degree Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills DevOps Engineering Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Available for Work Visa Sponsorship? Government Clearance Required? Job Posting End Date Are you ready to make a difference? Want to unlock new value by applying your unique perspective and talents? You can grow exponentially at PwC. Here, you can uncover hidden talents, build lifelong relationships rooted in trust and empathy and turn challenges into opportunities for innovation. We’ll help you grow your skills through challenging, meaningful work so you can go further.

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Responsibilities

The role involves designing, developing, and implementing end-to-end data solutions utilizing the Databricks Lakehouse platform architecture, including architecting data pipelines and optimizing data models using Delta Lake. Responsibilities also include developing robust ETL processes with Apache Spark, integrating Databricks SQL, and utilizing Databricks ML for AI/ML model deployment.