IN_Associate_Data Engineer_Data and Analytics_Advisory_Mumbai

Line of Service
Advisory

Industry/Sector
Not Applicable

Specialism
Data, Analytics & AI

Management Level
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: We are seeking a highly skilled and experienced Big Data Architect cum Data Engineer to join our dynamic team. The ideal candidate should have a strong background in big data technologies, designing the solutions and hands-on expertise in PySpark, Databricks, SQL. This position requires significant experience in building and managing data solutions in Databricks on Azure. The candidate should also have strong communication skills, experience in managing mid size teams, client conversations and presenting PoV and thought leadership.

Responsibilities: · Design and implement scalable big data architectures and solutions utilizing PySpark, SparkSQL, and Databricks on Azure or AWS. · Experience in building robust data models and maintain metadata-driven frameworks to optimize data processing and analytics. · Build, test, and deploy sophisticated ETL pipelines using Azure Data Factory and other Azure-based tools. · Ensure seamless data flow from various sources to destinations including ADLS Gen 2. · Implement data quality checks and validation frameworks. · Establish and enforce data governance principles ensuring data security and compliance with industry standards and regulations. · Manage version control and deployment pipelines using Git and DevOps best practices. · Provide accurate effort estimation and manage project timelines effectively.

· Collaborate with cross-functional teams to ensure aligned project goals and objectives. · Leverage industry knowledge in banking, insurance, and pharma to design tailor-made data solutions. · Stay updated with industry trends and innovations to proactively implement cutting-edge technologies and methodologies. · Facilitate discussions between technical and non-technical stakeholders to drive project success. · Document technical solutions and design specifications clearly and concisely. Qualifications: · Bachelor's degree in computer science, Engineering, or a related field. Master’s Degree preferred. · 8+ years of experience in big data architecture and engineering. · Extensive experience with PySpark, SparkSQL, and Databricks on Azure. · Proficient in using Azure Data Lake Storage Gen 2, Azure Data Factory, Azure Event Hub, Synapse. · Strong experience in data modeling, metadata frameworks, and effort estimation. · Experience of DevSecOps practices with proficiency in Git. · Demonstrated experience in implementing data quality, data security, and data governance measures. · Industry experience in banking, insurance, or pharma is a significant plus. · Excellent communication skills, capable of articulating complex technical concepts to diverse audiences. · Certification in Azure, Databricks or related Cloud technologies is a must. · Familiarity with machine learning frameworks and data science methodologies would be preferred.

Mandatory skill sets: Data Engineer/AWS

Preferred skill sets:

Data Engineer/AWS

Years of experience required:

3--5 years

Education qualification:

B.E.(B.Tech)/M.E/M.Tech

Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Bachelor Degree, Master Degree

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills
Data Engineering

Optional Skills
Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, 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, Data Quality, Data Strategy {+ 22 more}

Desired Languages (If blank, desired languages not specified)

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Job Posting End Date