The Senior Data Engineering Consultant plays a pivotal role in designing, deploying, and managing high-quality data solutions within the Azure and Snowflake cloud ecosystems. You will be responsible for creating and maintaining scalable data architectures, working in a collaborative Agile environment to define and deliver data engineering solutions, and guiding junior team members to adopt best practices. Design, deploy, and manage high-quality data solutions in Azure and Snowflake cloud ecosystems.

Key Responsibilities:

• Develop and maintain optimal data pipeline architectures.
• Collaborate with on-site and client stakeholders to define data engineering requirements and deliver solutions in an Agile environment.
• Continuously improve code quality and development practices to ensure reliable and scalable data services.
• Work alongside Data Engineers, Analysts, and Scientists to share expertise and mentor junior engineers in Azure and Snowflake best practices.
• Perform root cause analysis on internal and external data processes and communicate insights to stakeholders via reports and visualizations.
• Manage large datasets to meet functional and business requirements.

The ProCogia Mission

ProCogia aims to empower organizations to achieve sustainable advantage through data.

We enable our customers to make intelligent and agile decisions through strategically tailored data solutions. We attract, develop and retain diverse, motivated and collaborative team players who love what they do.

Our Values

TRUST We build trust in all of our relationships, internally and externally

GROWTH We believe in life-long learning; both personally and professionally

INNOVATION Our technology-agnostic & innovative approach enables cutting-edge data solutions

EXCELLENCE We are committed to delivering excellence in everything we do

Requirements

The Senior Data Engineering Consultant Cloud should have the following skills, education, and experience:

Skills Required:

• Expertise in Microsoft Azure cloud services and Snowflake for building scalable data pipelines and workflows.
• Experience with Azure Data Factory, Data Lake/Blob storage, Azure Functions, Dataflow, Databricks with PySpark, and Synapse Analytics.
• Proficient with Snowflake platform, SnowSQL, Snowpark, and Snowpipe.
• Strong skills in SQL, Python, and PySpark (Spark framework).
• Experience in enterprise Data Warehousing using both batch and real-time systems in cloud and on-prem environments.
• Expertise in data modeling within big data ecosystems.
• Familiarity with Synapse, Azure SQL Server, and Snowflake Data Warehouse.
• Understanding of API-based integration and security (RESTful/SOAP).
• Proficiency with data visualization tools such as Power BI, Tableau.
• Quick learner, with the ability to translate data into actionable insights.
• Strong communication skills for collaborating with both on-site teams and client stakeholders.

Preferred:

• Experience with Databricks preferred.
• Experience with Teradata, SQL Server
• Knowledge of Docker/containerization, IAM roles/policies.
• Solid Linux programming skills
• Stream-processing systems: Streaming-Analytics, IoT Hub, Event Hub, Kusto Queries (all nice to have)

Education

Required:

• Bachelors in a quantitative field such as computer science, computer engineering other related disciplines.

Preferred:

• Masters or PhD in a quantitative field such as computer science, computer engineering other related disciplines.

Experience

• An experienced professional will have at least 3+ years of professional experience in Data Engineering role with a Masters Degree or 5+ years of experience in a Data Engineering related role with a Bachelors degree

ProCogia is proud to be an equal opportunity employer. We are committed to creating a diverse and inclusive workspace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.