D&A - Senior Data Engineer

We are looking for a talented and experienced Mid-Level 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 ResponsibilitiesEnd-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 or Data Engineer/DBA - Must.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).Technical Knowledge: Practical experience with Delta Lake, file formats (Parquet), and working with Cloud Storage (AWS S3 / Azure ADLS).Modeling: Proven experience in designing Fact and Dimension tables.This position is open to all candidates.