2 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Develop AWS-based data engineering solutions for modern data platforms and client delivery workstreams.
- Build, test, and maintain cloud data pipelines, integrations, and transformation logic.
- Design scalable data models, data lakes, data warehouses, and structures supporting analytics and downstream applications.
- Use Apache Airflow, Databricks, Snowflake, Spark, and AWS services to orchestrate and optimize data processing.
- Troubleshoot performance, data quality, query, pipeline, and warehouse issues.
- Apply data architecture, validation, security, and access-control practices.
- Translate business and technical requirements into detailed designs and project deliverables.
- Review junior team members’ technical work and provide guidance on engineering methods and code quality.
- Incorporate client and project-lead feedback and contribute to cloud engineering and data modernization initiatives.
Requirements
- Bachelor’s degree or higher is required.
- At least 4 years of experience is required.
- Oral and written proficiency in English is required.
- Experience architecting and delivering scalable, distributed, cloud-based enterprise data solutions is required.
- Strong experience implementing AWS enterprise data lakes, data hubs, and cloud data engineering solutions is required.
- Hands-on Snowflake experience, including SnowSQL, Snowpipe, ETL pipelines, data sharing, events, and lakehouse patterns, is required.
- Experience with Python or Java, preferably also Scala, and with disparate data loading and detailed technical design is required.
- Experience with relational and NoSQL data stores, dimensional modeling, star and snowflake schemas, and data security and access controls is required.
- Knowledge of Lambda and Kappa architectures is required.
- Experience with Hadoop, Spark, Spark Core, Spark SQL, Spark Streaming, and performance tuning is required.
- Experience with AWS EMR, Glue, SageMaker, S3, Redshift, DynamoDB, and at least one of Kinesis, SQS, or MSK is required.
- Experience with Airflow, NiFi, or Luigi is required.
- Experience with Git, Jenkins or GitLab, and AWS CodePipeline, CodeBuild, or CodeCommit is required.
- Experience with CloudWatch, CloudTrail, AWS Account Config, and AWS Config Rules is required.
- Preferred fields of study include Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, and Mathematical Statistics.
- Preferred qualifications include AWS data engineering delivery, Apache Airflow, Databricks, Snowflake, data architecture, data modernization, and mentoring experience.
Benefits
- The role is based at the PwC Acceleration Center in Bangalore.
- The posting does not specify travel requirements.
- The posting does not state compensation or additional benefits.
Tech Stack
Amazon DynamoDBAmazon RedshiftApache AirflowApache HadoopApache SparkAWSDatabricksGitJavaJenkinsPythonScalaSnowflake
Categories
Data Engineering
About PwC
PwC is a global network of professional services firms providing assurance, tax, and advisory work for businesses and public-sector clients. It sells project-based and managed consulting, audit, and deals services, and implements and integrates business applications. Formed in 1998 by the merger of Price Waterhouse and Coopers & Lybrand, it is headquartered in London and is one of the Big Four accounting firms.