
Chief Data Infrastructure Specialist
2 days ago
We are looking for a Modern Data Engineer to design, build, and scale innovative data platforms on cloud-based infrastructure. As a senior member of our engineering team, you will work with Python, Spark, DBT, and cloud-native services in an Agile environment to deliver scalable, secure, and high-performance data solutions.
Key Responsibilities:- Develop and optimize ETL/ELT pipelines with Python, DBT, and cloud services.
- Build and manage cloud-based data lakes using modern data formats.
- Deliver end-to-end data solutions with Glue, EMR, Lambda, Redshift, and Athena.
- Implement strong metadata, governance, and security using Glue Data Catalog, Lake Formation, IAM, and KMS.
- Orchestrate workflows with Airflow, Step Functions, or cloud-native tools.
- Ensure reliability and automation with CloudWatch, CloudTrail, CodePipeline, and Terraform.
Collaborate with analysts and data scientists to deliver business insights in an Agile setting.
Requirements:- 7–10 years of experience in data engineering, with 4+ years on AWS platforms.
- Strong in Python (incl. AWS SDKs), DBT, SQL, and Spark.
- Proven expertise with AWS data stack (S3, Glue, EMR, Redshift, Athena, Lambda).
- Hands-on experience with workflow orchestration (Airflow/Step Functions).
- Familiarity with data lake formats (Parquet, ORC, Iceberg) and DevOps practices (Terraform, CI/CD).
- Solid understanding of data governance & security best practices.
Bonus: Exposure to Data Mesh principles and platforms like Data.World, familiarity with Hadoop/HDFS in hybrid or legacy environments.
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