Advisory
Not Applicable
Data, Analytics & AI
Senior Associate
At the firm, 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 the firm, 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.
At the firm, 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 the firm, 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. "
We are seeking skilled and dynamic Cloud Data Engineers specializing in AWS, Azure, Databricks, and GCP. The ideal candidate will have a strong background in data engineering, with a focus on data ingestion, transformation, and warehousing. They should also possess excellent knowledge of PySpark or Spark, and a proven ability to optimize performance in Spark job executions. Key Responsibilities: - Design, build, and maintain scalable data pipelines for a variety of cloud platforms including AWS, Azure, Databricks, and GCP. - Implement data ingestion and transformation processes to facilitate efficient data warehousing. - Utilize cloud services to enhance data processing capabilities: - AWS: Glue, Athena, Lambda, Redshift, Step Functions, DynamoDB, SNS. - Azure: Data Factory, Synapse Analytics, Functions, Cosmos DB, Event Grid, Logic Apps, Service Bus. - GCP: Dataflow, BigQuery, DataProc, Cloud Functions, Bigtable, Pub/Sub, Data Fusion. - Optimize Spark job performance to ensure high efficiency and reliability.
Python, Pyspark, SQL with (AWS or Azure or GCP)
Python, Pyspark, SQL with (AWS or Azure or GCP)
3-8 years
BE/BTECH, ME/MTECH, MBA, MCA
Degrees/Field of Study required: Master of Business Administration, Bachelor of Technology, Bachelor of Engineering
Degrees/Field of Study preferred:
AI Programming
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 {+ 28 more}
Not Specified
No
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