SENIOR ASSOCIATE DATA ENGINEER

The Senior Associate Data Engineer is a critical member of the engineering team, responsible for designing, building, and maintaining robust data systems and infrastructure. This role focuses on enabling efficient data processing, collection, storage, and analysis at scale to support data-driven decision-making and operational optimization.

What you'll do:

Data Architecture and Engineering:

• Build, Orchestrate and optimize data pipelines to extract, transform, and load (ETL) data from various sources into the organization's data warehouse or data lake.
• Integrate data from diverse sources such as databases, APIs, streaming platforms, and file systems into cohesive data pipelines
• Implement data integration solutions that support real-time, batch, and incremental data processing.
• Implement data quality checks and validation processes to ensure the accuracy, completeness, and consistency of data.
• Develop and maintain high-performance data pipelines that seamlessly integrate data from various sources into data warehouses, data lakes, and other storage solutions.
• Develop monitoring and alerting mechanisms to identify and address data quality issues proactively.
• Optimize ETL (Extract, Transform, Load) processes for efficiency, reliability, and data quality.
• Implement and manage data storage solutions, including relational databases, NoSQL databases, and distributed file systems.
• Manage the infrastructure and resources required to support data engineering workflows, including compute clusters, storage systems, and data processing frameworks
• Implement security controls and data governance measures for an application to protect sensitive data and ensure compliance with regulatory requirements such as GDPR, CCPA, HIPAA, and PCI-DSS. Implement encryption, access controls, and auditing mechanisms to safeguard data privacy and integrity..

Data Engineering Best Practices:

• Write production-ready, testable code that adheres to engineering best practices and accounts for edge cases and error handling.
• Ensure high-quality deliverables through code reviews, design reviews, and adherence to architectural guidelines.
• Develop comprehensive unit tests and integration tests to validate data pipeline functionality and data integrity.
• Stay up to date with the latest data engineering tools, technologies, and methodologies, and evaluate their applicability to the team's needs.

Technical Leadership and Collaboration:

• Provide technical guidance and mentorship to junior engineers on the team.
• Collaborate with data scientists, business analysts, and other stakeholders to understand data requirements and translate them into robust engineering solutions.
• Work closely with other engineering teams to integrate data solutions seamlessly into the overall technology ecosystem.
• Participate actively in agile ceremonies, communicate progress, and manage dependencies effectively.

What you'll bring:

Education: A relevant bachelor's or master's degree in computer science, Data Engineering, or a related technical field.

Technical Skills:

• Databricks (PySpark, Delta Lake, Unity Catalog)
• Azure Data Services (Data Lake, Data Factory, Synapse, Purview, Key Vault)
• SQL & Python for data engineering and analytics
• Data modeling (dimensional, relational, and modern lakehouse)
• Data governance & security (row-/column-level security, masking, tokenization)
• ETL/ELT pipeline design and orchestration
• Working knowledge of Power BI

Business & Consulting Skills

• Requirements gathering and documentation (BRDs, user stories, acceptance criteria)
• Participation in workshops with business and IT stakeholders to capture next steps and action items

Analytical & Domain Skills

• Understanding of data product principles and domain-driven design concepts

Experience:

• 4+ years of experience in a data engineering role, with a focus on building scalable, reliable, and high-performance data systems with Snowflake
• Proven track record of designing and implementing data pipelines, data storage solutions, and data processing workflows.
• Hands-on experience with distributed computing frameworks and cloud-based data services.
• Demonstrated ability to collaborate with cross-functional teams and communicate technical solutions effectively.
• Ability to travel to other offices or client locations as needed.
• Strong communication skills
• Fluency in English
• Client-first mentality
• Intense work ethic
• Collaborative spirit and problem-solving approach

How you'll grow:

• Cross-functional skills development & custom learning pathways
• Milestone training programs aligned to career progression opportunities
• Internal mobility paths that empower growth via s-curves, individual contribution and role expansions

Perks & Benefits:

At ZS, your growth matters. We offer a comprehensive total rewards package that supports your health and well-being, financial future, time away, and professional development. With robust skills-building programs, multiple career progression paths, internal mobility, and a deeply collaborative culture, you'll have the opportunity to do meaningful work, expand your capabilities, and thrive as part of a global community. For details on total rewards in Canada, visit ZS Canada office locations | Where we work | ZS.

Hybrid working model:

We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections.

Travel:

Travel is a requirement at ZS for client facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures.