Thoucentric - AWS Data Engineer - PySpark/SQL/Apache Airflow
3 weeks ago
About Us :
Thoucentric is the Consulting arm of Xoriant, a prominent digital engineering services company with 5000+ employees. We are headquartered in Bangalore with presence across multiple locations in India, US, UK, Singapore & Australia Globally.
As the Consulting business of Xoriant, We help clients with Business Consulting, Program & Project Management, Digital Transformation, Product Management, Process & Technology Solutioning and Execution including Analytics & Emerging Tech areas cutting across functional areas such as Supply Chain, Finance & HR, Sales & Distribution across US, UK, Singapore and Australia. Our unique consulting framework allows us to focus on execution rather than pure advisory. We are working closely with marquee names in the global consumer & packaged goods (CPG) industry, new age tech and start-up ecosystem. Xoriant (Parent entity) started in 1990 and is a Sunnyvale, CA headquartered digital engineering firm with offices in the USA, Europe, and Asia. Xoriant is backed by ChrysCapital, a leading private equity firm. Our strengths are now combined with Xoriants capabilities in AI & Data, cloud, security and operations services proven for 30 years.
We have been certified as "Great Place to Work" by AIM and have been ranked as "50 Best Firms for Data Scientists to Work For".
We have an experienced consulting team of over 450+ world-class business and technology consultants based across six global locations, supporting clients through their expert insights, entrepreneurial approach and focus on delivery excellence. We have also built point solutions and products through Thoucentric labs using AI/ML in the supply chain space.
Job Description :
Position Overview :
We are looking for an experienced AWS Data Engineer to design, develop, and maintain data solutions using core AWS services. The ideal candidate will have hands-on experience with tools like Amazon S3, Redshift, AWS Glue, and DynamoDB, and will build scalable, efficient, and secure data pipelines and architectures. The role also requires strong expertise in PySpark, SQL, and workflow orchestration tools like Airflow.
Key Responsibilities :
1. Data Pipeline Development :
- Develop and manage ETL/ELT workflows using AWS Glue and PySpark to process large datasets.
- Automate data workflows using Apache Airflow and other orchestration tools.
2. Data Storage and Management :
- Architect and manage data storage in Amazon S3 , ensuring performance, cost-efficiency, and security.
- Create and optimize Amazon Redshift clusters for data warehousing and analytics workloads.
- Design scalable NoSQL solutions using Amazon DynamoDB for real-time data needs.
3. Compute and Serverless :
- Build and deploy serverless solutions using AWS Lambda for event-driven data processing.
- Configure and manage virtual machine instances using Amazon EC2 for custom data processing tasks.
4. Security and Monitoring :
- Implement fine-grained access controls with AWS IAM to ensure data security.
- Set up monitoring, logging, and alerts using AWS CloudWatch for proactive system health management.
5. Data Integration and Transformation :
- Create efficient SQL queries to handle data transformations and analytics.
- Integrate and process structured and unstructured data from multiple sources.
- Design data models and implement them in Redshift or DynamoDB for optimized query performance.
6. Collaboration and Optimization :
- Collaborate with data scientists, analysts, and stakeholders to gather requirements and deliver solutions.
- Continuously optimize data processing workflows to improve performance and reduce costs.
Required Skills and Qualifications :
- Core AWS Expertise
- Strong knowledge of Amazon S3 , Redshift , AWS Glue , Lambda , DynamoDB , EC2 , IAM , and CloudWatch .
Technical Proficiency :
- Hands-on experience with PySpark for big data processing.
- Proficient in writing complex SQL queries for data manipulation and analysis.
- Expertise in workflow orchestration using Apache Airflow or similar tools.
Experience :
- 4+ years in data engineering with a focus on AWS technologies.
- Experience in designing scalable, fault-tolerant data pipelines.
- Familiarity with data modeling, ETL/ELT, and data warehousing principles.
Soft Skills :
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to manage priorities in a fast-paced environment
Note : For your candidature to be considered on this job, you need to apply necessarily on the company's redirected page of this job. Please make sure you apply on the redirected page as well.
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