• Maintain and optimize end-to-end ELT pipelines to ensure reliable, well-structured data flows into the warehouse. • Develop, test, and maintain scalable data models following modern data modeling and best practices. • Support data validation, testing, documentation, and governance across environments. • Contribute to metadata and lineage tracking, as well as standards for KPI modeling and data quality.

Data Engineer Location: US / Canada (Eastern Time) - Home based Job Type: Full-time, Permanent About AllCloud AllCloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, AllCloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation. AllCloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, AllCloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth. AllCloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io Job Summary Are you passionate about data and delivering solutions for clients that turn data into valuable, actionable information for their business? We are hiring Data Engineers with strong experience across the entire Cloud Data stack. The ideal candidate will have extensive experience in data pipelines (ELT/ETL), data replication, data warehousing and dimensional modeling, and curation of data sets for Data Scientists and Business Intelligence users. This candidate will also have excellent problem-solving ability dealing with large volumes of data. How You'll Make Your Mark: Building scalable Cloud data solutions using MPP Data Warehouses (Snowflake, Redshift, or Azure Data Warehouse/Synapse), data storage (S3, Azure Blob Storage, Delta Lakes, or AWS Lake Formation) and analytics platforms (i.e. Spark, Databricks, etc.) Creation of data pipelines and transformations Knowledge of ETL tools such as– Matillion, FiveTran, Informatica, Talend, SSIS, etc. Transformations – dbt Experience with elastic/open search Load historical data to a data warehouse Scripting in Python, Java Script or Shell Workflow Orchestrations using Apache Airflow, AWS Step Functions, etc. Familiarity with automated promotions, SCM tools, and CICD best practices Modeling and curation of data for visualization and predictive modeling users Design and implementation of AWS and/or Azure services such as Lambda, SNS, etc. Creating data integrations with scripting languages such as Python Writing complex SQL queries, stored procedures, etc. Summary of Requirements & Experience Experience working at a consulting company Experience with Data Vault architecture Matillion Associate Certification Snowflake SnowPro AWS Data & Analytics Specialty AWS Database Specialty AWS Solutions Architect Associate AWS Developer Associate AWS Glue Why work for us? Our team inspires progress in each other and in our customers through our relentless pursuit of excellence; you will work with leaders who promote learning and personal development. AllCloud is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, provincial, or local law.

• Design, implement, and manage complex DAGs and SubDAGs in Apache Airflow • Utilize Operators, macros, connections, variables, and xcom for efficient task execution • Conduct unit testing to ensure the robustness of Airflow workflows • Perform file operations and data movement between HDFS and S3 (and vice versa) • Manage Hive external tables, update table DDL, and handle partition operations • Execute basic Hadoop commands and navigate/traverse HDFS • Work with Hive on Tez for optimized query execution • Utilize AWS command line tools for tasks such as listing and copying files from S3 • Implement and manage secrets using tools like Ansible Vault and AWS Secrets Manager • Develop and optimize data processing tasks using PySpark • Understand and leverage Livy for efficient Spark job execution • Import and export data between Microsoft SQL Server and HDFS using Sqoop • Apply dimension modeling principles, define facts and dimensions, and manage surrogate keys • Implement effective branching strategies in Git • Participate in the process of raising and reviewing Merge Requests in GitLab • Utilize SSIS for migrating data workflows, ensuring a smooth transition • Model data in Snowflake, differentiating between external and internal tables • Understand the use of views and materialized views in Snowflake

• Design and develop scalable cloud data infrastructure and pipelines. • Build and maintain data pipelines and infrastructure for Lakehouse systems. • Collaborate with cross-functional teams in a Scrum environment. • Implement data management frameworks and align with Veracyte’s global data strategy. • Optimize data retrieval, processing, and ELT workflows. • Mentor junior data engineers and foster a culture of continuous learning.