Data Platform Engineer

Data Platform Engineer# Data Platform Engineer1001 Industrial Parkway McDonough - McDonough, GA 30253## OverviewPosition TypeFull TimeJob ShiftDay 8-5Education Level4 Year DegreeTravel Percentage0-25%CategoryStrategy - Planning## Description# Data Platform Engineer| | | || --- | --- | --- || **Department:**Data & Analytics | **Location:**Hybrid | **Employment Type:**Full-Time |## Position OverviewWe are seeking an experienced Data Engineer to join our growing team and play a central role in shaping our data strategy. This individual will be responsible for building, optimizing, and governing our Databricks-based data platform hosted on AWS connecting disparate data sources, enabling reliable data pipelines, and ensuring that high-quality data is available to support business intelligence, analytics, and machine learning initiatives.## Key Responsibilities**Data Strategy & Platform Governance*** Partner with leadership to define and execute a comprehensive data strategy aligned with business goals.* Establish standards and best practices for data ingestion, transformation, storage, and access across the organization.* Drive adoption of data governance frameworks including data cataloging, lineage tracking, and quality monitoring.* Champion a culture of data-driven decision-making by enabling self-service analytics capabilities.**Databricks Platform Administration*** Architect, configure, and maintain the Databricks environment hosted on AWS (EMR, S3, IAM, VPC, etc.).* Manage Databricks workspaces, clusters, Unity Catalog, and access controls.* Optimize compute and storage costs through cluster sizing, auto-scaling, and lifecycle management.* Implement and maintain CI/CD pipelines for data workflows using tools**Data Integration & Pipeline Development*** Design and build scalable ETL/ELT pipelines to ingest data from a variety of sources including SaaS applications, databases, APIs, and streaming platforms.* Leverage Delta Lake, Delta Live Tables, and Databricks Workflows to build reliable, incremental data processing solutions.* Integrate cloud-native AWS services (Glue, Kinesis, EventBridge, Lambda) with the Databricks ecosystem.* Ensure data pipeline reliability through monitoring, alerting, and automated recovery mechanisms.**Collaboration & Data Enablement*** Partner with data analysts, data scientists, and business stakeholders to understand data requirements and deliver fit-for-purpose datasets.* Develop and maintain data documentation, including data dictionaries, runbooks, and architecture diagrams.* Mentor junior team members on best practices in data engineering and cloud-native development.## Qualifications## Required Qualifications**Technical Skills**| | || --- | --- || | * 5+ years of hands-on data engineering experience in a cloud environment. || | * Strong proficiency with Databricks (Notebooks, Workflows, Delta Lake, Unity Catalog, SQL Warehouses). || | * Deep expertise with AWS services: S3, IAM, VPC, Glue, Redshift, RDS, Lambda, Kinesis, or EventBridge. || | * Proficiency in Python for data engineering workloads; SQL expertise required. || | * Experience designing and building data lake / lakehouse architectures. || | Familiarity with data transformation tooling such as dbt, Apache Spark, or similar frameworks. || | * Knowledge of data modeling concepts (dimensional modeling, data vault, or medallion architecture). |**Experience & Education**| | || --- | --- || | * Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience. || | * Proven track record of delivering end-to-end data platform solutions at scale. || | * Experience with infrastructure-as-code tools such as Terraform is a strong plus. || | * Databricks Certified Associate or Professional certification preferred. || | * AWS Certified Data Analytics or Solutions Architect certification preferred |**We are not able to consider candidates who will require sponsorship at any point during employment.** #J-18808-Ljbffr