People Consulting-Analytics-Senior

The opportunity

We are seeking a Senior Data Engineer with strong Python expertise to join our team. The core purpose is to design, build, and maintain the data infrastructure and pipelines that support the organization's business intelligence and analytics.

Your key responsibilities

•  Designing and implementing data pipelines that reliably process large volumes of data
•  Managing and optimizing data infrastructure and systems
•  Ensuring data quality, security, and compliance
•  Collaborating with stakeholders to understand data requirements
•  Troubleshooting and maintaining production systems

Skills and attributes for success

• Technical Foundation: Need strong programming skills, particularly in Python, with hands-on experience building real systems in production environments. Should be comfortable working with modern data platforms like Databricks and be proficient in tools that orchestrate data workflows.
• Data Infrastructure Knowledge: Understanding how data flows through systems are essential. This includes knowledge of databases, data warehouses, data lakes, architectures—essentially knowing different ways to store and organize data at scale.
• Cloud Proficiency: You need practical experience with major cloud providers (AWS, Azure, or GCP) and their data services, as modern data engineering happens almost exclusively in the cloud.
• Problem-Solving Mindset: The role requires analytical thinking to design efficient solutions and troubleshoot issues when systems fail or perform poorly.

To qualify for the role, you must have

• Python expertise: 5+ years of hands-on work in production environments. You should be able to write clean, efficient code at scale.
• Python data libraries: Proficiency with Pandas, NumPy, SQL Alchemy, and PySpark for data manipulation and processing.
• Workflow orchestration: Experience with tools like Apache Airflow, Prefect, or Luigi that automate and schedule data jobs.
• SQL and Databases: Solid SQL skills and familiarity with both relational databases (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Cassandra).
• Cloud platforms: Working knowledge of AWS, Azure, or GCP data services.
• Data Lake and Lakehouse concepts: Understanding how to structure and manage large-scale data storage systems.
• Git: Version control expertise for code management and collaboration.

Ideally, you’ll also have

• Education: A bachelor's or master's degree in computer science, engineering, or a related field
• Advanced Databricks Skills: Knowledge of Databricks ML flow for machine learning pipelines, Databricks SQL, and BI tool integrations. This shows you can work across the analytics and machine learning spectrum
• Open-source Contributions: Active contributions to open-source Python projects. This demonstrates engagement with the tech community and software engineering best practices.
• Data Science Knowledge: Understanding of data science concepts and machine learning workflows, which shows breadth beyond just engineering.

What we look for

EY People Consulting is likely seeking someone who:

• Has a proven track record of shipping data systems to production
• Balances technical depth with practical business awareness
• Can communicate across technical and non-technical audiences
• Is proactive about learning and staying current with evolving technologies
• Works well in teams and takes pride in enabling others' success