Sr Data Engineer

Tailored Brands, Inc.; Cambridge; On-site; CAD 120,000 - 180,000; Full time

Job summary

Tailored Brands, Inc. seeks a senior Data Engineer to design, assess, and support efficient data pipelines across Snowflake, BigQuery, Oracle, and other platforms. You will automate large-scale data ingestion, ensure scalability, and own the end-to-end data solutions.

You will mentor junior engineers, collaborate with data scientists and business partners, and help maintain SLAs and data quality in production environments.

Qualifications

• 8+ years of experience in a data engineering or platform role.
• Strong understanding of software engineering best practices (agile, coding standards, testing, reviews).
• Hands-on experience in cloud-based data warehouse and ETL/ELT solutions with APIs and external data sources.
• Proven ability to develop scalable, reliable data pipelines as volume grows.
• Proficiency in SQL and scripting languages (Python, PySpark, Bash).
• Experience with Snowflake and Google Cloud Platform / AWS; data modeling and ETL/ELT tools.

Responsibilities

• Design, assess and support efficient, reliable data pipelines across enterprise systems.
• Automate large-scale data ingestion and transformations across diverse data sources.
• Owns designs and implementations, ensuring performance, standards, and scalability.
• Collaborate with data scientists, analytics teams and business partners to deliver data solutions.
• Mentor junior engineers and support production operations; monitor data quality and SLAs.
• Adapt to changing data needs and timelines while maintaining reliability.

Skills

Data pipelines

SQL

Python

PySpark

Bash

Airflow

Kubernetes

CI/CD

Data modeling

Cloud platforms

Education

Bachelor's or Master's in CS/AI Engineering

Tools

Fivetran

HVR

Airflow

Automic UC4

GitHub

Jenkins

Kubernetes

Ansible

Job description

Design, assess and support efficient, reliable data pipelines that move data across enterprise systems including Snowflake, BigQuery,Oracle, AS400, SQL Server, Salesforce and external partner platforms using API's, AWS S3, and GCP buckets. Enhance and scale cloud-based data warehousing and ETL capabilities to automate large-scale data ingestion and transformation across diverse data sources. Identify opportunities to automate, optimize, and modernize existing data processes to improve performance, reliability, and productivity. Own the solutions and designs you build, ensuring they meet operational standards, performance expectations, and long-term scalability. Contribute to strong data operations environment by adhering to SLAs, improving data quality, and implementing monitoring and automation best practices. Collaborate closely with data scientists, analytics teams, and business partners to deliver data solutions that support reporting, analytics, and predictive use cases. Mentor and coach junior engineers by providing technical guidance, design feedback, and supporting production operations. Adapt quickly to changing business priorities and data needs while meeting delivery timelines and supporting production operations.

• Bachelor's or Master's degree in Computer Science,or AI Engineering, or a related field.
• 8+ years of experience in a data engineering or platform role, ideally working with large, complex datasets; retail industry experience a plus.
• Strong understanding of software engineering best practices, including agile development, coding standards, code reviews, testing, and operational support.
• Hands-on experience designing, building, and enhancing cloud-based data warehouse and ETL/ELT solutions, including integration with Application Programming Interfaces (APIs) and external data sources.
• Proven ability to develop scalable, accurate, and timely data pipelines as data volume and complexity grow.
• Proficiency in engineering and automating batch and streaming data pipelines, including data mappings and transformations.
• Strong experience with cloud platforms inluding Snowflake,bigquery on AWS and GCP, with proficiency in SQL, and scripting/programming languages such as Python, PySpark, and Bash.
• Strong experience optimizing Snowflake performance using query profiling, virtual warehouse tuning, clustering keys, Search Optimization Service, Query Acceleration Service, caching, and cost optimization best practices.
• Strong experience with data modeling, data warehousing environments, and ETL/ELT tools such as Fivetran, HVR, or similar platforms.
• Strong experience writing complex SQL queries and optimizing performance in Snowflake and relational databases such as Snowflake, bigquery,Oracle or MySQL.
• Strong experience of CI/CD practices and tools (e.g., GitHub, Jenkins, Kubernetes, Ansible) for production deployments.
• Experience supporting DSAR and regulatory compliance (GDPR/CCPA) using Snowflake data governance, masking policies, RBAC, data lineage, and secure data access controls Ability to independently troubleshoot and resolve complex production and data quality issues.
• Strong experience supporting analysts and data scientists with query optimization, performance tuning, and data processing.
• Strong experience with workflow orchestration and scheduling tools such as Airflow or Automic UC4 is a plus.
• Experience implementing data governance using Snowflake Horizon or Atlan, RBAC, masking policies, data lineage, metadata management, and enterprise security best practices.
• Experience implementing data quality frameworks using automated validation, monitoring, reconciliation, and observability tools such as Anamolo, Great Expectations, or custom SQL/Python checks.
• Exposure to business intelligence tools such as power bI,essbase or MicroStrategy is advantageous.
• Strong communication and interpersonal skills, with the ability to collaborate effectively across technical and non-technical teams.
• A proactive mindset with the ability to identify improvement opportunities and present recommendations to leadership.
• Ability to sit and work at a computer keyboard for extended periods of time Ability to stoop, kneel, bend at the waist, and reach daily