Senior Data Engineer

Job summary

Design, build, and optimize scalable Snowflake-based data platforms, pipelines, data products, and integrations, ensuring performance, quality, security, lineage, and governance. Collaborate with business stakeholders and AI and analytics teams, support automated engineering workflows, contribute to architecture standards, and mentor junior engineers.

Job details

Description This is a temporary contractor position for an existing vacancy. About the Role We are seeking a highly skilled Senior Data Engineer to join our growing Data & AI Marketplace team. In this role, you will be responsible for designing, building, and optimizing scalable enterprise data solutions that power advanced analytics, AI, and business intelligence initiatives across the company. As part of our strategic transformation, you will play a key role in building and advancing our Snowflake-based Enterprise Data Platform, enabling self-service analytics, AI solutions, and governed data products that create measurable business value. This is an exciting opportunity for an experienced data professional who enjoys solving complex data challenges, modernizing data architectures, and working closely with business stakeholders, architects, data scientists, and AI engineers. Key Responsibilities Design, develop, and maintain scalable data pipelines using Snowflake and cloud-native technologies. Build and optimize ELT/ETL processes for structured, semi-structured, and unstructured data sources. Develop enterprise-grade data models, data products, and reusable datasets. Implement data integration solutions across enterprise systems, APIs, cloud platforms, and operational applications. Collaborate with Data Scientists and AI Engineers to support machine learning and generative AI initiatives. Develop and maintain data ingestion frameworks, orchestration workflows, and metadata management processes. Optimize Snowflake performance through clustering, partitioning, query tuning, and cost management strategies. Ensure data quality, security, lineage, and governance requirements are embedded into all solutions. Support CI/CD implementation and automation of data engineering workflows. Participate in architecture reviews and contribute to enterprise data standards and best practices. Mentor junior data engineers and contribute to the growth of the Data & AI engineering community. Required Qualifications Bachelor’s degree in computer science, Engineering, Information Systems, or a related discipline. 8+ years of experience in Data Engineering, Data Warehousing, or Analytics Engineering. 3+ years of hands-on experience with Snowflake in enterprise environments. Strong experience building modern cloud-based data platforms. Advanced SQL development and performance tuning expertise. Proficiency in Python for data engineering and automation. Experience designing and implementing large-scale data pipelines. Strong understanding of dimensional modeling, data warehousing concepts, and data lake architectures. Experience with source control, DevOps, and CI/CD practices. Excellent communication and stakeholder management skills. Preferred Qualifications Snowflake SnowPro Certification (Core or Advanced). Hands-on experience with: Snowpark Cortex AI Dynamic Tables Streams & Tasks Data Sharing Iceberg Tables Zero-Copy Cloning Experience integrating Snowflake with: Azure Databricks Microsoft Fabric Power BI Informatica Kafka Experience supporting AI, machine learning, or generative AI workloads. Knowledge of utility, energy, or regulated industry environments. Familiarity with data governance, privacy, and security frameworks. Technical Skills: Data Platforms Snowflake (Expert) Azure Data Services Data Lake Architecture Enterprise Data Warehousing Programming Python SQL Shell Scripting Data Integration & Orchestration Airflow Azure Data Factory Informatica REST APIs DevOps & Engineering Git CI/CD Pipelines Terraform (preferred) Infrastructure as Code Analytics & AI Enablement Power BI Machine Learning Pipelines Generative AI Data Preparation Data Marketplace Concepts What Success Looks Like In your first year, you will: Deliver high-quality data products on the Enterprise Data Platform. Enable AI and analytics use cases through trusted, governed data assets. Optimize Snowflake performance, reliability, and cost efficiency. Establish reusable engineering patterns that accelerate data and AI delivery. Contribute to building a scalable Data & AI Marketplace that empowers business teams through self-service access to trusted data. This role operates under a hybrid work model and requires employees to work from the office a minimum of two days per week.

What you’ll do

Design, build, and optimize scalable Snowflake-based data platforms, pipelines, data products, and integrations, ensuring performance, quality, security, lineage, and governance. Collaborate with business stakeholders and AI and analytics teams, support automated engineering workflows, contribute to architecture standards, and mentor junior engineers.

Requirements

Requires a bachelor’s degree in computer science, engineering, information systems, or a related discipline, at least eight years of data engineering or related experience, and at least three years of hands-on enterprise Snowflake experience. Candidates should have advanced SQL and Python skills, experience with cloud data platforms, large-scale pipelines, data warehousing and lake architectures, and source control and CI/CD practices.

Listed skills

• SQL · Preferred
• CI/CD · Preferred
• Machine learning · Preferred
• Git · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Snowflake
• SQL
• Python
• Data Engineering
• Data Warehousing
• Data Modeling
• ETL/ELT
• Data Pipelines
• Azure Data Services
• Airflow
• Azure Data Factory
• Informatica
• Git
• CI/CD
• Data Governance
• Machine Learning

Job areas

• Data & Analytics
• Technology
• Software
• Engineering

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