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AWS Data Architect

Mango AnalyticsAustin, TX🇺🇸United StatesPosted 16 Jul 2026

Why This Role Stands Out

Elevate your career as an AWS Data Architect at Mango Analytics, where you'll shape impactful data strategies and drive innovation within a reputable tech company. If you're a skilled professional with expertise in Python, Airflow, and AWS services, and you thrive in a collaborative hybrid environment, this is an excellent opportunity to grow your technical leadership. Embrace this chance to contribute to cutting-edge projects and advance your career in data architecture.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

AWS Architect

Location : Austin, TX – Hybrid 2 -3 days per week

 

 

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

                     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 efficient data storage, retrieval, and analysis.

Skills

AWS
Airflow
Kafka
Python
Redshift

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