Data Engineer (AWS / Snowflake) - Senior Consultant
Deloitte View all jobs
- Canada
- $72,000-138,000 per year
- Permanent
- Full-time
This role is ideal for a hands-on Senior Consultant who combines strong technical capabilities with strategic thinking, and a passion for building modern data ecosystems.Key Responsibilities
Strategy
- Define the data engineering roadmap aligned to business priorities, cloud strategy, and enterprise architecture standards.
- Establish best practices, coding standards, and governance frameworks for data engineering across AWS and Snowflake ecosystems.
- Architect and oversee the development of scalable data pipelines leveraging AWS services (e.g., Glue, Lambda, S3, Step Functions, Redshift) and/or Snowflake.
- Direct the design and implementation of robust ETL/ELT frameworks with a strong focus on performance, security, and maintainability.
- Ensure enterprise-wide data integration across internal and external systems, enabling high-quality, trusted data flows.
- Support the implementation of automated data quality, data profiling, and data validation frameworks.
- Champion automation to improve reliability, reduce operational overhead, and eliminate manual data-processing steps.
- Oversee the development of cleansing, transformation, and enrichment strategies using SQL, Python, and other relevant tools.
- Drive continuous optimization of data pipelines for cost efficiency, performance, and reliability.
- Establish monitoring, alerting, and incident management processes.
- Maintain clear documentation for architecture, workflows, pipelines, and operational procedures.
- Partner with business stakeholders, analytics teams, and data governance groups to understand requirements and deliver scalable solutions.
- Communicate progress, risks, and technical decisions to leadership and cross-functional partners.
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
- 3+ years of hands-on experience in data engineering, including ETL/ELT development and cloud data platforms.
- Strong expertise in AWS data services (e.g., Glue, Lambda, EMR, Step Functions, S3).
- Proven experience designing, implementing, and optimizing solutions in Snowflake (warehousing, performance tuning, cost management, security).
- Advanced proficiency in SQL and scripting languages (Python preferred).
- Solid understanding of modern data architecture practices: data lakes, lakehouses, orchestration, CI/CD, and metadata management.
- Experience with data integration, data quality, and data observability frameworks.
- Excellent communication and problem solving skills.
- Experience with big data technologies (Spark, Hadoop, EMR, Databricks).
- Knowledge of data governance, data lineage, and data security frameworks.
- Familiarity with modern orchestration tools (Airflow, dbt, Dagster).
- AWS or Snowflake certifications (Data Engineer, Solutions Architect, SnowPro).
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