Highlights
Ingest and process large-scale data from diverse enterprise sources, including databases, APIs, message queues, and file-based systems. " Collaborate with business, analytics, architecture, and delivery teams in an Agile environment to deliver high-quality data products.
Numbers & Facts
| Location | Frederick, MD |
| Industry | Computer/IT Services |
| Company Size | 500 to 999 employees |
| Year Founded | 1990 |
| Website | http://q1tech.com/ |
Description
Responsibilities
" Design, develop, and maintain scalable, high-performance data engineering solutions on Azure Databricks.
" Build and support batch and real-time data pipelines using Apache Spark and Structured Streaming.
" Design and implement Lakehouse and Medallion Architecture (Bronze, Silver, Gold) using Delta Lake.
" Develop reusable ETL/ELT frameworks, standardized data processing components, and enterprise data ingestion patterns.
" Ingest and process large-scale data from diverse enterprise sources, including databases, APIs, message queues, and file-based systems.
" Develop complex data transformation logic using PySpark, Python, and SQL.
" Create trusted, governed, and consumption-ready datasets for reporting, analytics, and downstream applications.
" Implement data quality, validation, reconciliation, audit, and governance controls across data pipelines.
" Manage and optimize Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, and Databricks SQL.
" Collaborate with business, analytics, architecture, and delivery teams in an Agile environment to deliver high-quality data products.
Required Technical Skills:
Databricks & Data Engineering
" Strong hands-on experience with Databricks, Lakehouse Architecture, and Delta Lake
" Expertise in PySpark, Python, and advanced SQL
" Experience with Apache Spark, Structured Streaming, Delta Live Tables (DLT), Databricks Workflows, and Unity Catalog
" Experience designing and implementing Medallion Architecture and modern Data Lake/Data Warehouse solutions
" Strong background in data ingestion, ETL/ELT, data transformation, optimization, and deployment practices
" Experience with event-driven and streaming technologies such as Kafka or Azure Event Hub
Cloud Platforms
" Microsoft Azure (preferred)
" AWS or GCP experience is also valuable
Application Integration
" Working knowledge of React and/or Angular for front-end integration and data-centric application development
Domain Experience (Preferred)
" Experience in Finance, Insurance, Regulatory Reporting, or US GAAP reporting
" Understanding of financial data models, reporting processes, and governance requirements is highly desirable
** Mandatory to work from office only
" Design, develop, and maintain scalable, high-performance data engineering solutions on Azure Databricks.
" Build and support batch and real-time data pipelines using Apache Spark and Structured Streaming.
" Design and implement Lakehouse and Medallion Architecture (Bronze, Silver, Gold) using Delta Lake.
" Develop reusable ETL/ELT frameworks, standardized data processing components, and enterprise data ingestion patterns.
" Ingest and process large-scale data from diverse enterprise sources, including databases, APIs, message queues, and file-based systems.
" Develop complex data transformation logic using PySpark, Python, and SQL.
" Create trusted, governed, and consumption-ready datasets for reporting, analytics, and downstream applications.
" Implement data quality, validation, reconciliation, audit, and governance controls across data pipelines.
" Manage and optimize Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, and Databricks SQL.
" Collaborate with business, analytics, architecture, and delivery teams in an Agile environment to deliver high-quality data products.
Required Technical Skills:
Databricks & Data Engineering
" Strong hands-on experience with Databricks, Lakehouse Architecture, and Delta Lake
" Expertise in PySpark, Python, and advanced SQL
" Experience with Apache Spark, Structured Streaming, Delta Live Tables (DLT), Databricks Workflows, and Unity Catalog
" Experience designing and implementing Medallion Architecture and modern Data Lake/Data Warehouse solutions
" Strong background in data ingestion, ETL/ELT, data transformation, optimization, and deployment practices
" Experience with event-driven and streaming technologies such as Kafka or Azure Event Hub
Cloud Platforms
" Microsoft Azure (preferred)
" AWS or GCP experience is also valuable
Application Integration
" Working knowledge of React and/or Angular for front-end integration and data-centric application development
Domain Experience (Preferred)
" Experience in Finance, Insurance, Regulatory Reporting, or US GAAP reporting
" Understanding of financial data models, reporting processes, and governance requirements is highly desirable
** Mandatory to work from office only
About Company
Q1 consists of experienced and recognized experts providing the capability to respond to market demand in order to provide professional services for our clients including Enterprise software implementations, application integration and technical / functional support.
Q1 has steadily grown into a Quality IT services and solutions organization with the average experience of our team being over 10 years. We have continuously met or exceeded client expectations by delivering professional services and project implementations on time and under budget to help clients truly recognize return on investment.
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