Data Analyst/Engineer

A Data Analyst is responsible for gathering, analyzing and problem solving as it relates to data, types of data, and relationships among data elements within a business system or IT system and with business domain subject matter expertise.

A Data Analyst provides expertise on how Business workflows map to data, and how data can be integrated to build reusable data products. A Data analyst will serve as a subject matter expert for delivery teams. A Data analyst will serve as a subject matter expert for delivery teams.

Responsibilities for this position may include but are not limited to:

• Understanding the business use of data and stakeholder requirements to support work processes and strategic business objectives.

• Working with business (digital platform, Business Units, function teams) and delivery teams to provide data management direction and support for data foundation initiatives and data products development.

• Analyzing current data management: process, practices, tools, and helping shape future needs. Contributing to the design of common information models.

• Assessing data quality concerns specific to workflow solutions being adopted and driving mitigation activities.

• Advising on the appropriate data integration patterns, data modeling and data quality.

• Maintaining and sharing knowledge of requirements, key data types and data definitions, data stores, data creation process.

• Knowledge of Finance data and SAP are an advantage

Technical Skills:

• Familiarity with technologies such as Azure SQL, Python, and Power BI.
• Data Catalog/Lineage (Purview), Data Modeling Techniques, Data fluency/modeling, Ability to use different data visualizations techniques and apply them appropriately.
• Fundamental knowledge of Information Risk Management (IRM)
• Knowledge and/or experience with Cloud computing, data collection, cleaning and preparation, business process and data modeling, data strategy, policies, and governance.

Align and Inspire:

• Proven skill in being the link between different stakeholder groups (e.g., IT & Business) to collect, express and clarify requirements, while also matching goals & expectations among stakeholders to produce work products.

Build Relationships:

• Build trusted working relationships with peers and stakeholders (internal & external parties) across global teams and time zones while seeking ways to maintain a work life balance through asynchronous communications.
• Collaborate within an agile mindset and seek/acknowledge diverse perspective from others

-- DATA ENGINEER --

A Data Engineer designs data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective. Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.

As a Data Engineer, you will:

• Design, develop, and maintain data pipelines and ETL processes using Microsoft Azure services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks, Azure Fabric).

• Utilize Azure data storage accounts for organizing and maintaining data pipeline outputs.  (e.g., Azure Data Lake Storage Gen 2 & Azure Blob storage).

• Collaborate with data scientists, data analysts, data architects and other stakeholders to understand data requirements and deliver high-quality data solutions.

• Optimize data pipelines in the Azure environment for performance, scalability, and reliability.

• Ensure data quality and integrity through data validation techniques and frameworks.

• Develop and maintain documentation for data processes, configurations, and best practices.

• Monitor and troubleshoot data pipeline issues to ensure timely resolution.

• Stay current with industry trends and emerging technologies to ensure our data solutions remain cutting-edge.

• Manage the CI/CD process for deploying and maintaining data solutions.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience) and able to demonstrate high proficiency in programming fundamentals.

• Proven experience (3+ years) as a Data Engineer or similar role dealing with data and ETL processes.

• Strong knowledge of Microsoft Azure services, including Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage and Azure Data Lake Gen 2.

• Experience utilizing SQL DML to query modern RDBMS in an efficient manner (e.g., SQL Server, PostgreSQL).

• Strong understanding of Software Engineering principles and how they apply to Data Engineering (e.g., CI/CD, version control, testing).

• Experience with big data technologies (e.g., Spark).

• Strong problem-solving skills and attention to detail.

• Excellent communication and collaboration skills.

Preferred Qualifications:

• Learning agility

• Technical Leadership

• Consulting and managing business needs

• Strong experience in Python is preferred but experience in other languages such as Scala, Java, C#, etc. is accepted.

• Experience building spark applications utilizing PySpark.

• Experience with file formats such as Parquet, Delta, Avro.

• Experience efficiently querying API endpoints as a data source.

• Understanding of the Azure environment and related services such as subscriptions, resource groups, etc.

• Understanding of Git workflows in software development.

• Using Azure DevOps pipeline and repositories to deploy and maintain solutions.

• Understanding of Ansible and how to use it in Azure DevOps pipelines.