Position Responsibilities / Accountabilities:

• Implements and enhances complex data processing pipelines with a focus on collecting, parsing, cleaning, managing and analyzing large data sets that produce valuable business insights and discoveries.
• Determines the required infrastructure, services, and software required to build advanced data ingestion & transformation pipelines and solutions in the cloud.
• Assists data scientists and data analysts with data preparation, exploration and analysis activities.
• Applies problem solving experience and knowledge of advanced algorithms to build high-performance, parallel, and distributed solutions.
• Performs code and solution review activities and recommends enhancements that improve efficiency, performance, stability, and decreased support costs.
• Applies the latest DevOps and Agile methodologies to improve delivery time.
• Works with SCRUM teams in daily stand-up, providing progress updates on a frequent basis.
• Supports application, including incident and problem management.
• Performs debugging and triage of incident or problem and deployment of fix to restore services.
• Documents requirements and configurations and clarifies ambiguous specs
• Performs other duties as assigned by management.

Minimum Requirements:

• 3+ years of experience working in large-scale data integration and analytics projects, using AWS cloud (e.g. AWS Redshift, S3, EC2, Glue, Kinesis, EMR), big data (Hadoop) and orchestration (e.g. Apache Airflow) technologies
• 3 years with Languages: SQL, Python, Spark
• 3+ years of experience in implementing distributed data processing pipelines using Apache Spark
• 3+ years of experience in designing relational/NoSQL databases and data warehouse solutions

Nice to have, but not required:

• 2+ years of experience in writing and optimizing SQL queries in a business environment with large-scale, complex datasets
• 2+ years of Unix/Linux operating system knowledge (including shell programming).
• 2+ years of experience in automation/configuration management tools such as Terraform, Puppet or Chef.
• 2+ years of experience in container development and management using Docker.
• 2+ years of experience in continuous integration tools (e.g. Jenkins).
• Basic knowledge of machine learning algorithms and data visualization tools such as Microsoft Power BI and Tableau

INDHCLSMC

Nearest Major Market:
New York City


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Cloud, Database, SQL, Linux, Unix, Technology