Data Architect

Saransh Inc; Hartford (CT); On-site; USD 120,000 - 160,000; Full time

Job summary

Saransh Inc is seeking a Data Architect for an onsite contract role in Hartford, CT and Minneapolis, MN. You will lead the design and implementation of scalable data architectures on AWS, leveraging Spark for batch processing and Flink for real-time streams, with a focus on data modeling, governance, and end-to-end pipelines.

The position requires hands-on experience with Python, Docker, Kubernetes, CI/CD, and both SQL and NoSQL databases.

Qualifications

• Strong hands-on Python for data engineering and app development.
• Experience with AWS services including S3, EMR, Glue, Lambda, IAM, EC2, ECS/EKS, CloudWatch, Redshift.
• Expertise in Apache Spark for large-scale batch processing.
• Hands-on with Apache Flink for real-time streaming and data pipelines.
• Experience designing batch and streaming architectures and data modeling.

Responsibilities

• Design and implement scalable, secure data architectures on AWS.
• Build and optimize batch processing pipelines with Apache Spark.
• Develop real-time streaming solutions using Apache Flink.
• Define data models, governance standards, and best practices.
• Shape end-to-end data ingestion, transformation, and processing pipelines.

Skills

Python

AWS

Apache Spark

Apache Flink

SQL

Docker

Kubernetes

Git

CI/CD

Tools

Docker

Kubernetes

Git

CI/CD

Job description

Position Title: Data Architect
Location: Minneapolis, MN & Hartford, CT (Onsite)
Duration: 6 Months Contract

Job Description:

• Strong hands-on experience in Python for data engineering and application development.
• Extensive experience with AWS cloud services, including S3, EMR, Glue, Lambda, IAM, EC2, ECS/EKS, CloudWatch, and Redshift.
• Strong expertise in Apache Spark for large-scale batch data processing.
• Hands‑on experience with Apache Flink for real‑time stream processing and event‑driven data pipelines.
• Experience designing and implementing batch and streaming data architectures.
• Strong knowledge of data modeling, data warehousing, and data lake/lakehouse concepts.
• Experience with ETL/ELT frameworks and data integration.
• Strong SQL skills and experience with relational and NoSQL databases.
• Experience with Apache Kafka or similar messaging/event streaming platforms.
• Strong understanding of distributed computing and big data technologies.
• Experience with Docker, Kubernetes, and CI/CD pipelines.
• Hands‑on experience with Git and Agile development methodologies.
• Design and implement scalable, secure, and high‑performance data architecture solutions on AWS.
• Build and optimize batch processing pipelines using Apache Spark.
• Develop real‑time streaming data solutions using Apache Flink.
• Design end‑to‑end data ingestion, transformation, and processing pipelines.
• Define data models, governance standards, and architectural best practices.
• Python, Apache Spark, AWS, Apache Flink, batch and streaming data architectures, ETL/ELT, Apache Kafka, Docker, Kubernetes, CI/CD pipelines.