
Chief Data Architect
1 week ago
We are seeking experienced professionals to lead our data engineering efforts.
- Develop and implement efficient ETL/ELT workflows to process structured, unstructured, and streaming data in cloud environments.
- Leverage cloud services like AWS S3, Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, Athena, DynamoDB, RDS, and Lake Formation for scalable data ingestion, transformation, storage, and querying.
- Ensure robust data governance, security, and quality controls throughout the data lifecycle, supporting regulatory compliance.
- Enable both real-time and batch data processing pipelines to power AI-driven workflows and applications.
- 3–7 years of hands-on experience in Data Engineering, building data pipelines, and cloud-based data solutions.
- Strong programming skills in Python, SQL, and/or Scala/Java.
- Expertise in AWS cloud services, including S3, Glue, EMR, Redshift, Athena, Kinesis, Lambda, Step Functions, DynamoDB, and RDS.
- Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, Dagster, or similar.
- Collaborate closely with AI/ML teams to prepare clean, high-quality datasets optimized for model training, inference, and fine-tuning.
- Optimize data infrastructure to achieve high performance, scalability, reliability, and cost efficiency.
- Implement CI/CD pipelines and data engineering best practices in a cloud-native architecture for automated deployments.
This role requires a strong foundation in data engineering principles, cloud computing, and software development. The ideal candidate will have a proven track record of designing and implementing scalable data pipelines and architectures.
What We Offer:- A collaborative and dynamic work environment.
- Opportunities for professional growth and development.
- A competitive salary and benefits package.
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