AWS Data Architect

🕒 May 15

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EXL

10,000+ employees

💰 $2M Venture Round on 2015-01

Choosing a digital partner is about more than capabilities — it’s about collaboration and character.

📋 Description

‱ Develop and maintain a comprehensive data architecture and cloud strategy that aligns with the organization's goals and needs. ‱ Design, implement, and manage cloud-based data infrastructure on AWS, ensuring scalability, reliability, and cost-efficiency. ‱ Utilize AWS services (S3, Glue, EMR, Redshift, Lambda, Kinesis, MWAA, etc.) to build and optimize data pipelines and storage solutions. ‱ Champion the use of data lakehouse architecture and optimize its performance for analytical and operational workloads. ‱ Identify the gaps and opportunities in the current system and suggest/implement to optimise the processes and costs. ‱ Lead and guide data engineering teams to develop, maintain, and optimize ETL processes for data ingestion, transformation, and loading. ‱ Implement real-time data processing solutions using technologies such as Apache Kafka and AWS Kinesis. ‱ Collaborate with data scientists, business stakeholders and analysts to ensure data availability and quality, enabling effective analytics and reporting. ‱ Leverage DBT for data modelling and transformation to support self-service analytics and data governance. ‱ Architect and implement data integration solutions for API ingestion, enabling data from diverse sources to be captured, transformed, and ingested into our data lakehouse. ‱ Utilize Airbyte and custom APIs to ensure efficient, reliable, and secure data transfers. ‱ Manage data integration pipelines to support real-time and batch data processing. ‱ Design, configure, and maintain workflow orchestration using Apache Airflow to automate ETL processes and data pipeline executions. ‱ Monitor and optimize job scheduling, error handling, and performance of data workflows. ‱ Implement data security protocols, access controls, and encryption to safeguard sensitive data, especially PIIs. ‱ Ensure compliance with data privacy regulations and industry standards. ‱ Collaborate with cross-functional teams to understand data requirements and provide data solutions to meet their needs. ‱ Maintain comprehensive documentation for data engineering and data architecture processes and solutions. ‱ Guide the team in setting up cloud Infra and automate using tools like terraform, cloud formation, Jenkins etc ‱ Guide the operations team in setting up automated monitoring & alerts mechanism

🎯 Requirements

‱ Bachelor's or higher degree in a relevant field. ‱ 6+ years of proven experience in data engineering, cloud architecture, and AWS services. ‱ Extensive knowledge of data lakehouse technologies, Hudi, DBT, Airbyte, Redshift, Glue, Kinesis and Apache Airflow. ‱ Strong expertise in programming languages like SQL, Python and processing frameworks like PySpark ‱ Strong expertise in real-time data processing. ‱ Excellent problem-solving and analytical skills. ‱ Strong communication and teamwork abilities. ‱ Passion for Sports/Gaming/Entertainment is preferred

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