DECAL Analytics Engineer

Under general supervision, combines strong technical skills with knowledge of the database administration. Works on one or more projects of high complexity.

The Analytics Engineer will contribute to our modern data estate strategy by developing scalable data solutions using Microsoft Fabric and Azure Databricks. This role will be instrumental in building resilient data pipelines, transforming raw data into curated datasets, and delivering analytics-ready models that support enterprise-level reporting and decision-making.

Work Location & Attendance Requirements:

Must be physically located in Georgia

On-site: Tuesday to Thursday, per manager's discretion

Mandatory in-person meetings:

o All Hands

o Enterprise Applications

o On-site meetings

o DECAL All Staff

Work arrangements subject to management's decision

Key Responsibilities:

Data Engineering & Pipeline Development

Build and maintain ETL/ELT pipelines using Azure Databricks and Microsoft Fabric.

Implement medallion architecture (Bronze, Silver, Gold layers) to support data lifecycle and quality.

Develop real-time and batch ingestion processes from IES Gateway and other source systems.

Ensure data quality, validation, and transformation logic is consistently applied.

Use Python, Spark, and SQL in Databricks and Fabric notebooks for data transformation.

Delta Lake: Implementing Delta Lake for data versioning, ACID transactions, and schema enforcement.

Integration with Azure Services: Integrating Databricks with other Azure services like Azure One Lake, Azure ADLS Gen2, and Microsoft fabric.

Data Modeling & Curation

Collaborate with the Domain Owners to design dimensional and real-time data models.

Create analytics-ready datasets for Power BI and other reporting tools.

Standardize field naming conventions and schema definitions across datasets.

Data Governance & Security

Apply data classification and tagging based on DECAL s data governance framework.

Implement row-level security, data masking, and audit logging as per compliance requirements.

Support integration with Microsoft Purview for lineage and metadata management.

Data Modeling:

Dimensional modeling

Real-time data modeling patterns

Reporting & Visualization Support

Partner with BI developers to ensure data models are optimized for Power BI.

Provide curated datasets that align with reporting requirements and business logic.

Create BI dashboards and train users.

DevOps & Automation

Support CI/CD pipelines for data workflows using Azure DevOps.

Assist in monitoring, logging, and performance tuning of data jobs and clusters.

Required Qualifications:

Bachelor s degree in computer science, Data Engineering, or related field.

3+ years of experience in data engineering or analytics engineering roles.

Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization.

Hands-on experience with:

o Azure Databricks (Spark, Delta Lake)

o Microsoft Fabric (Dataflows, Pipelines, OneLake)

o SQL and Python (Pandas, PySpark)

o SQL Server 2019+

Familiarity with data modeling, data governance, and data security best practices.

Strong understanding of ETL/ELT processes, data quality, and schema design.

Preferred Skills:

Experience with Power BI datasets and semantic modeling.

Knowledge of Microsoft Purview, Unity Catalog, or similar governance tools.

Exposure to real-time data processing and streaming architectures.

Knowledge of federal/state compliance requirements for data handling

Familiarity with Azure DevOps, Terraform, or CI/CD for data pipelines.

Certifications (preferred):

Microsoft Fabric Analytics Engineer.

Soft Skills:

Strong analytical and problem-solving abilities.

Excellent communication skills for technical and non-technical audiences.

Experience working with government stakeholders.

Required/Desired Skills

Skill Required /Desired Amount of Experience
3+ years of experience in data engineering or analytics engineering roles.	Required	3	Years
Advanced SQL: Proficiency in advanced SQL techniques for data transformation, querying, and optimization.	Required	3	Years
Azure Databricks (Spark, Delta Lake)	Required	3	Years
Microsoft Fabric (Dataflows, Pipelines, OneLake)	Required	3	Years
SQL and Python (Pandas, PySpark)	Required	3	Years

Questions

No. Question
Question1	Absences greater than two weeks MUST be approved by CAI management in advance, and contact information must be provided to CAI so that the resource can be reached during his or her absence. The Client has the right to dismiss the resource if he or she does not return to work by the agreed upon date. Do you agree to this requirement?
Question2	What is your candidate's email address?
Question3	If selected for engagement, your candidate's hourly Pay Rate $$.$$ $$.$$ $$.$$ $$.$$ must be at least $$.$$. Your candidate can be paid more; however, the hourly SRP Rate $$.$$ $$.$$ $$.$$ cannot exceed $$.$$. Do you agree to these requirements?
Question4	The maximum mark-up for this engagement s SRP rate is XX%. To be competitive on pricing, a mark-up below the 35% threshold is suggested. Do you agree to propose a mark-up at or below 35%?
Question5	This assignment is contingent upon customer renewal and availability of adequate funding. Do you agree to this requirement?
Question6	If selected for engagement, your candidate will be expected to start no later than 2 weeks (10 business days) after the client's selection date? Do you agree to this requirement?