Data Solutions Specialist
3 weeks ago
This role is responsible for designing, deploying, and maintaining data solutions that meet the business requirements of the Metropolitan Transportation Authority. The Data Engineer will work closely with data analysts, data scientists, and other stakeholders to gather requirements and build data pipelines that facilitate accurate and timely data availability for analysis and decision-making.
Key Responsibilities
Design, develop, and implement data solutions to meet business requirements and data ingestion needs
Extract, load, and transform (ELT/ETL) data from various sources, including on-premises and cloud-based systems, APIs, databases, and files
Write well-designed, efficient code that adheres to security standards
Monitor and troubleshoot data pipelines to identify and resolve issues promptly to minimize disruptions in data processing for on-premises and cloud environments
Implement data quality checks and validation processes to ensure accuracy and completeness of data
Collaborate with the data team to resolve data quality issues
Continuously optimize data pipelines for performance, scalability, and reliability
Requirements
Bachelor's Degree
At least 3 years of relevant experience
Strong knowledge of Big Data architectures, large data warehouses, and Data Lake solutions
Experience designing and implementing Modern Data and Analytics solutions, including Lakehouse architecture and medallion architecture
Proficient in cloud services, including Azure Databricks, Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Store, Microsoft Purview, and Power BI
Experience deploying and running cloud-based data solutions and infrastructure-as-code frameworks like Terraform
Proficient in cloud deployments (MS Azure preferred) in an agile SDLC environment, leveraging modern programming languages, and DevOps
Experience with major database platforms, including Oracle, SQL Server, as well as Cloud databases and NOSQL Databases
Strong understanding of data engineering concepts, ELT/ETL principles, and data modeling
Experience with data integration techniques for both structured and unstructured data
Solid programming skills in languages such as Python, Pyspark, and SQL
Experience with Airflow
Experience in DevOps, Git Repos, and CI/CD pipelines for code deployment
Experience deploying and administering cloud-based data solutions using infrastructure-as-code and infra-automation tools like Terraform, Ansible, etc.
Experience with Microsoft Purview is a plus
Strong knowledge of Microsoft Azure Cloud, AWS, and GCP are desirable
Functional knowledge of Microsoft Power BI
Experience with Jira, Confluence
Demonstrated ability to work independently and navigate organizational ambiguity
Effective written and verbal communication skills
Hands-on programming experience in a business setting
Proficiency in at least one software engineering methodology, including but not limited to Agile, Scrum, DevOps, Extreme Programming (XP), Kanban, Lean, and Rapid Application Development (RAD)
Experience applying structured validation and testing methods, including but not limited to Unit Testing, Integration Testing, System Testing, Acceptance Testing, and Regression Testing
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