Data Engineer-I

Posted 2 days agoViewed

📍 Location: USA

🔍 Industry: Healthcare

🗣️ Languages: English

🪄 Skills: PythonSQLBashETLMicrosoft AzurePostgresData modeling

Collaborate with team, management, departments using virtual tools
Run Production data pipelines/processes, ensure the integrity of the data, and send out deliverables based on requirement/runbook documentation
Coordinate with the various technical teams to resolve issues/bugs/optimize said production processes
Coordinate with internal client facing team members to communicate the status of deliverables
Help develop/improve technical documentation to guide future software development projects and operations
Dedicated time to explore building out tech stack and capabilities where there are applicable use cases
Provide critical thinking, technical innovation, and extra attention to detail by serving as a trusted team member and peer code reviewer
Assists with external client communications when deliverables or receivables do not meet technical or project requirements, ensuring timely resolution and alignment

Posted 15 days ago

📍 United States

🧭 Full-Time

💸 90000.0 - 110000.0 USD per year

🔍 Software Development

🔧 Requirements

BS/BA in Computer Science, Physics/Engineering, Business or Mathematics
Experience in building ETL data pipelines, real-time pipelines are a plus
Strong programming skills in Python and SQL
Minimum 2 years of data warehouse development and strong fundamentals in dimensional data modeling
Minimum 2 years of experience creating SQL queries and ETL design, implementation, and maintenance
Minimum 2 years of experience developing data pipelines using Python
Minimum 2 years of experience with AWS, AWS Redshift, AWS Data Engineering and ML Ops tools and services (i.e: S3, Redshift, RDS)
Proven ability to aggregate, normalize, munge, analyze, and summarize value from disparate datasets
Strong oral, written, and interpersonal communication skills
High degree of accuracy and attention to detail
Ability to establish priorities and work independently with minimum supervision

💡 Responsibilities

Collaborate with stakeholders to understand data requirements and develop data-driven solutions that support business goals
Analyze data sources and pipelines needed for the various data projects
Design and implement scalable data pipelines, ETL processes, and data integration solutions for the IRIS project using Python, SQL, and AWS technologies
Develop and maintain a data warehouse and optimize data storage, processing, and retrieval
Build schema, populate the database, and automate reporting
Document and maintain technical specifications, ETL processes, data mappings, and dictionaries
Support the Data Science Center of Excellence (DSCOE) with other data engineering needs

AWSPythonSQLETLData modeling

Posted 15 days ago

Posted about 2 months ago

📍 U.S.

💸 142500.0 - 155000.0 USD per year

🔍 Music technology

🔧 Requirements

5+ years of experience building scalable and durable software.
Demonstrated mastery of Python, SQL, and Unix fundamentals.
Operational excellence in maintaining Data Warehouses such as GCP BigQuery or AWS RedShift.
Strong familiarity with data transformation frameworks like sqlmesh or dbt.
Experience with business intelligence platforms or data visualization frameworks like Looker, Hashtable, or Observable.
Strong debugging skills, especially with distributed systems.
Experience building supporting Cloud Infrastructure with Google Cloud Platform (GCP) and Amazon Web Services (AWS).
Clear and consistent communication in a distributed environment.

💡 Responsibilities

Own and operate the structure of the Data Warehouse, ensuring reliable ingestion of mission-critical data and reliable builds of our pipelines.
Build and maintain self-service tools and extensible datasets for organizational insights.
Identify and execute projects addressing scalability issues, automating workflows, and simplifying datasets for analytics.
Ensure data quality through tests, observability, RFC reviews, and guidance in data modeling.
Participate in business hours-only on-call rotation to maintain system uptime and quality.
Cultivate a culture of data literacy and data-driven decision making.

AWSPythonSQLGCPData engineeringData visualizationDebugging

Posted about 2 months ago