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
We are looking for a talented and experienced Data Engineer with a passion for data and cloud technologies to join our team. In this role, you will be a key player in designing, developing, and maintaining our AWS and Databricks-based data platform. You will bridge the gap between robust Data Engineering, Database Administration (DBA), and high-performance Analytics Engineering.
The ideal candidate understands the Lakehouse architecture, has experience managing modern cloud data warehouses like Snowflake, and possesses the ability to build scalable ETL pipelines that drive data-driven business decisions.
Key Responsibilities
End-to-End Pipelines: Develop and maintain complex ETL/ELT pipelines using Python/PySpark on the Databricks platform, as well as loading and transforming data within Snowflake.
Data Architecture: Implement and manage data layers following the Medallion architecture (Bronze, Silver, Gold) using Delta Lake.
Optimization & Analytics: Set up and manage Databricks SQL Warehouses, perform query optimization, and utilize internal visualizations for rapid data exploration.
Cloud Infrastructure: Leverage AWS cloud services to manage data storage, compute resources, and secure data movement.
DBA & Performance Tuning: Act as a custodian for our data platform—managing indexing, clustering, vacuuming, and performance tuning across both Delta Lake and relational/warehouse environments to ensure cost-efficiency and high speed.
Data Modeling: Design data models (Star Schema / Snowflake) in the Gold layer to ensure optimal performance for BI tools (e.g., Power BI, Tableau).
Data Governance: Manage metadata, permissions, and lineage using Unity Catalog and platform-specific access controls.
Quality Control: Implement automated Data Quality tests as an integral part of the CI/CD data pipelines.
Requirements
5+ years of experience as a Data Engineer – Must.
Cloud & Warehouse Expertise: Strong hands-on experience with the AWS ecosystem (S3, IAM, EC2, etc.) and modern cloud data warehouses, specifically Snowflake.
At least 1 year of intensive, hands-on experience with the Databricks platform (including Notebooks and Workflows).
High proficiency in PySpark (or Spark Scala).
Expertise in writing complex SQL (Window Functions, CTEs) alongside DBA-level performance tuning (query profiling, indexing, partition pruning).
Practical experience with Delta Lake, file formats (Parquet), and working with Cloud Storage (AWS S3 / Azure ADLS).
Proven experience in designing Fact and Dimension tables.
Advantages (Nice to Have)
Experience with Delta Live Tables (DLT) or dbt (Data Build Tool) on Databricks or Snowflake.
Familiarity with MLOps concepts and MLflow.
Official AWS, Snowflake, or Databricks Certifications.
Experience with external orchestration tools (e.g., Apache Airflow).
Soft Skills
Ability to work independently and lead tasks end-to-end in an Agile environment.
Strong troubleshooting skills for complex, distributed processes and database bottlenecks.
Excellent communication skills and the ability to collaborate with various stakeholders (Analysts, Product Managers, and Data Scientists).
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.
