Senior Data Engineer on-site)

Ziosk•Plano, TX

61d•Onsite

About The Position

Welcome to Ziosk, where we empower restaurants to focus on what matters most: the guest experience! Have you ever used a tablet to pay at a restaurant? We pioneered the pay-at-the-table concept and we’re cooking up a plan to transform the restaurant industry. Our recipe for success has been adapting and growing to exceed the needs of our clients, such as Olive Garden, Texas Roadhouse, Chili’s and more – helping them create an experience that keeps guests coming back. Today we have a full menu of solutions, from hardware to software to cloud-based and AI driven products, all focused on helping them create the best guest experience possible to grow their bottom line. Our secret sauce? Our people! Every day, they’re cooking up bold solutions, making Ziosk the leading pay-at-the-table provider in the industry. Want a seat at our table? Ziosk is looking for a highly skilled and experienced Senior Data Engineer with deep expertise in Azure Databricks to contribute to the design, development, and optimization of our modern data platform. In this role, you will be responsible for building scalable ETL pipelines, implementing data lakehouse architectures, and supporting advanced analytics use cases in a high-volume data environment. You will work closely with data architects, data scientists, business stakeholders, and cloud infrastructure teams to deliver reliable, secure, and high-performance data solutions.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5+ years of experience in data engineering, with 3+ years focused on Azure Databricks and Spark (PySpark).
Expertise in Delta Lake, Unity Catalog, Databricks Notebooks, and SQL Warehousing.
Hands-on experience with Azure cloud services: ADLS Gen2, Event Hub, ADF, Key Vault, Synapse.
Strong programming skills in Python, SQL, and familiarity with Scala.
Solid understanding of data modeling (OLTP/OLAP), star/snowflake schemas, and performance tuning.
Experience with CI/CD pipelines in Databricks using Databricks CLI, Terraform, or Azure DevOps.
Candidates must be eligible to work in the U.S. and be able to commute to Plano, TX daily.
Applicants must be authorized to work for any employer in the U.S.

Nice To Haves

Databricks certification (e.g., Databricks Certified Data Engineer Professional).
Experience with real-time streaming (e.g., using Structured Streaming, Event Hub, Kafka).
Familiarity with MLflow or machine learning pipeline support in Databricks.
Experience with Power BI, Azure Purview, or Microsoft Fabric for downstream reporting.
Knowledge of data governance, lineage, and compliance standards (GDPR, HIPAA, SOC2).

Responsibilities

Design and implement scalable ETL/ELT pipelines using Azure Databricks (PySpark, Spark SQL).
Build robust data ingestion workflows from diverse sources (Event Hub, APIs, Azure SQL, Blob Storage, etc.) into the Bronze/Silver/Gold layers of the medallion architecture.
Define and implement best practices for Delta Lake and Unity Catalog for schema evolution, versioning, and governance.
Optimize performance and cost efficiency of large-scale data pipelines through intelligent partitioning, caching, clustering, and tuning Spark configurations.
Integrate Databricks with Azure Data Lake Storage (ADLS Gen2), Azure Data Factory (ADF), Azure Synapse, Event Hub, Key Vault, and Azure DevOps.
Implement secure and governed access to data using managed identities, role-based access control (RBAC), and data masking techniques.
Partner with data analysts, data scientists, and business users to understand data needs and deliver trusted datasets and KPIs.
Provide technical leadership and mentorship to junior engineers, conducting code reviews and guiding architectural decisions.
Collaborate with enterprise architects and InfoSec to ensure compliance with data security and privacy policies.
Implement data quality checks, alerts, and lineage tracking using tools such as Great Expectations, Unity Catalog, and Data Observability platforms.
Set up monitoring dashboards, alerts, and job recovery mechanisms for mission-critical pipelines.