What are the responsibilities and job description for the Senior. Data Engineer position at CARE IT Services Inc?
Job Summary:
The Senior Data Engineer will be responsible for building and maintaining the data infrastructure that powers the organization's data-driven decision-making. Designs, develops, and maintains data pipelines, data warehouses, and other data-related infrastructure. This role expects to work closely with data scientists, analysts, and other stakeholders to understand their data needs and translate them into robust and scalable solutions.
Key Responsibilities:
Build, maintain, and optimize data pipelines, including ELT processes, data models, reports, and dashboards to drive business insights.
Develop and implement data solutions for enterprise data warehouses and business intelligence (BI) initiatives.
Continuously monitor and optimize data pipelines for performance, reliability, and cost-effectiveness. This includes identifying bottlenecks, tuning queries, and scaling infrastructure as needed.
Automate data ingestion, processing, and validation tasks to ensure data quality and consistency.
Implement data governance policies and procedures to ensure data quality, consistency, and compliance with relevant regulations.
Contribute to the development of the organization's overall data strategy.
Conduct code reviews and contribute to the establishment of coding standards and best practices.
Required Qualifications:
Bachelor's degree in a relevant field or equivalent professional experience.
4-6 years of hands-on experience in data engineering.
Strong expertise in SQL and NoSQL databases, including PostgreSQL, DynamoDB, and MongoDB.
Experience working with cloud platforms such as GCP, Azure, or AWS and their associated data services.
Practical knowledge of data warehouses like BigQuery, Snowflake, and Redshift.
Programming skills in Python or JavaScript.
Proficiency with BI tools such as Sisense, Power BI, or Tableau.
Preferred Qualifications:
Direct experience with Google Cloud Platform (GCP).
Knowledge of CI/CD pipelines, including tools like Docker and Terraform.
Background in the healthcare industry.
Familiarity with modern data integration tools such as DBT, Matillion, and Airbyte.
The Senior Data Engineer will be responsible for building and maintaining the data infrastructure that powers the organization's data-driven decision-making. Designs, develops, and maintains data pipelines, data warehouses, and other data-related infrastructure. This role expects to work closely with data scientists, analysts, and other stakeholders to understand their data needs and translate them into robust and scalable solutions.
Key Responsibilities:
Build, maintain, and optimize data pipelines, including ELT processes, data models, reports, and dashboards to drive business insights.
Develop and implement data solutions for enterprise data warehouses and business intelligence (BI) initiatives.
Continuously monitor and optimize data pipelines for performance, reliability, and cost-effectiveness. This includes identifying bottlenecks, tuning queries, and scaling infrastructure as needed.
Automate data ingestion, processing, and validation tasks to ensure data quality and consistency.
Implement data governance policies and procedures to ensure data quality, consistency, and compliance with relevant regulations.
Contribute to the development of the organization's overall data strategy.
Conduct code reviews and contribute to the establishment of coding standards and best practices.
Required Qualifications:
Bachelor's degree in a relevant field or equivalent professional experience.
4-6 years of hands-on experience in data engineering.
Strong expertise in SQL and NoSQL databases, including PostgreSQL, DynamoDB, and MongoDB.
Experience working with cloud platforms such as GCP, Azure, or AWS and their associated data services.
Practical knowledge of data warehouses like BigQuery, Snowflake, and Redshift.
Programming skills in Python or JavaScript.
Proficiency with BI tools such as Sisense, Power BI, or Tableau.
Preferred Qualifications:
Direct experience with Google Cloud Platform (GCP).
Knowledge of CI/CD pipelines, including tools like Docker and Terraform.
Background in the healthcare industry.
Familiarity with modern data integration tools such as DBT, Matillion, and Airbyte.
