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PwC

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3.4

based on 9k Reviews

Video summary

13 PwC Data Engineer Jobs

Data Engineer (Snowflake/Databricks) -Specialist-Operate

Pricewaterhouse Coopers Private Limited

3.4

based on 9k Reviews

1-5 years

₹ 6 - 23.2583L/yr (AmbitionBox estimate)

Bangalore / Bengaluru

1 vacancy

Data Engineer (Snowflake/Databricks) -Specialist-Operate

PwC

posted 1mon ago

Job Role Insights

Flexible timing

Key skills for the job

SQL Project Management Auditing Analytical Chemistry SAP Business Intelligence Business Operations

+ 4 more

Job Description

A career in our Managed Services team will provide you with an opportunity to collaborate with a wide array of teams to help our clients implement and operate new capabilities, achieve operational efficiencies, and harness the power of technology. Our Data, Testing & Analytics as a Service team brings a unique combination of industry expertise , technology, data management and managed services experience to create sustained outcomes for our clients and improve business performance. We empower companies to transform their approach to analytics and insights while building your skills in exciting new directions. Have a voice at our table to help design, build and operate the next generation of software and services that manage interactions across all aspects of the value chain.

Minimum Degree Required (BQ) *

Bachelors degree

Degree Preferred

Required Field(s) of Study (BQ)

Preferred Field(s) of Study

Computer and Information Science, Management Information Systems

Minimum Year(s) of Experience (BQ) * US

Minimum of 1 year of experience

Certification(s) Preferred

Preferred Skills (PQs)

We are looking for skilled AWS and Snowflake Production Support Specialists to join our dynamic IT team. In these roles, you will be responsible for ensuring the availability, performance, and security of our AWS cloud infrastructure and Snowflake data platform. You will play a critical role in monitoring, troubleshooting, and resolving incidents to minimize downtime and support our business operations.

Responsibilities

Candidate is expected to demonstrate extensive knowledge and/or a proven record of success in the following areas

Should have minimum 1 year of hand on experience building advanced Data warehousing solutions on leading cloud platforms.

Should have minimum 1year of Operate/Managed Services/Production Support Experience

Should have extensive experience in developing scalable, repeatable, and secure data structures and pipelines to ingest, store, collect, standardize, and integrate data for downstream consumption like Business Intelligence systems, Analytics modeling, Data scientists etc.

Designing and implementing data pipelines to extract, transform, and load (ETL) data from various sources into data storage systems, such as data warehouses or data lakes.

Should have experience in building efficient ETL/ELT processes using industry leading tools like Informatica, Talend, SSIS, AWS, Azure, Spark, SQL, Python etc.

Should have Handson experience with Data analytics tools like Informatica, Collibra, Hadoop, Spark, Snowflake etc.

Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.

Work together with data scientists and analysts to understand the needs for data and create effective data workflows.

Create and maintain data storage solutions including Azure SQL Database, Azure Data Lake, and Azure Blob Storage.

Utilizing Azure Data Factory or comparable technologies, create and maintain ETL (Extract, Transform, Load) operations.

Perform data transformation and processing tasks to prepare the data for analysis and reporting in Azure Databricks or Azure Synapse Analytics for largescale data transformations using tools like Apache Spark.

Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.

Improve the scalability, efficiency, and costeffectiveness of data pipelines.

Monitoring and troubleshooting data pipelines and resolving issues related to data processing, transformation, or storage.

Implementing and maintaining data security and privacy measures, including access controls and encryption, to protect sensitive data

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases

Should have experience in Building and maintaining Data Governance solutions (Data Quality, Metadata management, Lineage, Master Data Management and Data security) using industry leading tools

Scaling and optimizing schema and performance tuning SQL and ETL pipelines in data lake and data warehouse environments.

Should have Handson experience with Data analytics tools like Informatica, Collibra, Hadoop, Spark, Snowflake etc.

Should have Experience of ITIL processes like Incident management, Problem Management, Knowledge management, Release management, Data DevOps etc.

Should have Strong communication, problem solving, quantitative and analytical abilities.

Nice to have

Azure certification

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required

Degrees/Field of Study preferred

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Accepting Feedback, Accepting Feedback, Active Listening, Automation, Automation Framework Design and Development, Automation Solutions, Budgetary Management, Business Process Automation (BPA), Business Process Improvement, Business Process Outsourcing, Business Transformation, Communication, Continuous Process Improvement, Data Quality Automation, Deliverable Planning, Delivery Excellence, Design Automation, Digital Transformation, Emotional Regulation, Empathy, Inclusion, Intellectual Curiosity, Managed Services, Operational Excellence, Operational Performance Management (OPM) {+ 19 more}

Travel Requirements

Available for Work Visa Sponsorship?

Government Clearance Required?

Employment Type: Full Time, Permanent

Read full job description

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What Data Engineer at PwC are saying

3.1

Rating based on 21 Data Engineer reviews

Anonymous · Data Science & Analytics in Kolkata

Likes

Pro: 1. Excellent team culture, always appreciative and friendly environment 2. Flexible work hours. No strict timings. 3. Hybrid mode of work. 2-3 days in office / week.

Skill development - Excellent

+3 more

Dislikes

Cons: 1. Poor appraisals and promotions 2. Too much approvals and MBA controlled, no freedom to explore as a technical person. 3. People have almost zero technical knowledge. Specially the mid level.