Job location : Gachibowli, Hyderabad.

Work mode : Work from office (all 5 days)

Role : AWS Data Architect

AWS Services, Python, Pyspark, EDW data modelling, Data Arch

Skills : Python, Airflow, S3, Spark(Glue, EMR), Kafka (SQS, Event Bridge), Integration (AppFlow, APIs), AWS Services, Redshift, EMR, DW Concepts & Data Modelling experience

Candidate should possess a deep understanding of big data technologies, cloud services, and data architecture, with a proven track record of leading data-driven projects to successful completion.

Key Responsibilities

- Lead a team of data engineers, providing technical guidance and mentorship.
- Develop and execute a strategic roadmap for data processing, storage, and analytics in alignment with organizational goals.
- Design, implement, and maintain robust data pipelines using Python and Airflow, ensuring efficient data flow and transformation for analytical and operational purposes.
- Utilize AWS services, including S3 for data storage, Glue and EMR for data processing, and orchestrate data workflows that are scalable, reliable, and secure.
- Implement real-time data processing solutions using Kafka, SQS, and Event Bridge, addressing high-volume data ingestion and streaming needs.
- Oversee the integration of diverse systems and data sources through AppFlow, APIs, and other integration tools,



ensuring seamless data exchange and connectivity.
- Lead the development of data warehousing solutions, applying best practices in data modelling to support productive data storage, retrieval, and analysis.
- Continuously monitor, optimize, and troubleshoot data pipelines and infrastructure, ensuring optimal performance and scalability.
- Ensure adherence to data governance, privacy, and security policies, implementing measures to protect sensitive data and comply with regulatory requirements.

Qualifications

- Bachelors or Masters degree in Computer Science, Engineering, or a related field.
- 8-10 years of experience in data engineering, with at least 3 years in a leadership role.
- Proficient in Python programming and experience with Airflow for workflow management.
- Strong expertise in AWS cloud services, particularly in data storage, processing, and analytics (S3, Glue, EMR, etc.).
- Experience with real-time streaming technologies like Kafka, SQS, and Event Bridge.
- Solid understanding of API based integrations and familiarity with integration tools such as AppFlow.
- Deep knowledge of data warehousing concepts, data modelling techniques, and experience in implementing large scale data warehousing solutions.

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