Senior Data Engineer (Developer)

Dallas, TX, US • Posted 60+ days ago • Updated 11 hours ago

Full Time

On-site

USD 145,000.00 per year

Fitment

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Job Details

Skills

Shared Services
Decision-making
Data Architecture
Unstructured Data
Data Warehouse
Microservices
Apache Airflow
Streaming
Automated Testing
Advanced Analytics
Training
A/B Testing
Generative Artificial Intelligence (AI)
Machine Learning (ML)
Data Governance
Meta-data Management
Data Masking
Encryption
Access Control
Auditing
Query Optimization
Resource Management
Root Cause Analysis
Data Quality
Leadership
Mentorship
Technical Drafting
Knowledge Sharing
Data Engineering
Database
Computer Science
Information Technology
Management
Apache Spark
PySpark
Java
Apache Hadoop
Real-time
Apache Kafka
Amazon Kinesis
Data Storage
SQL
NoSQL
PostgreSQL
MongoDB
Apache Cassandra
Data Modeling
Warehouse
Dimensional Modeling
Snow Flake Schema
SCD
Extract
Transform
Load
ELT
Data Flow
Terraform
Orchestration
Docker
Kubernetes
Apache HTTP Server
Machine Learning Operations (ML Ops)
Workflow
Amazon SageMaker
Vector Databases
Splunk
Grafana
Continuous Integration
Continuous Delivery
DevOps
GitHub
Jenkins
Cloud Computing
Python
C#
Scala
High Availability
Conflict Resolution
Problem Solving
Communication
Microsoft Azure
Data Processing
Microsoft
Analytics
Amazon Web Services
Databricks
Graph Databases
Regulatory Compliance
Privacy
Artificial Intelligence
Collaboration
Innovation

Summary

Senior Data Engineer (Developer) In-office position
Salary: Up to $145K
Location: Dallas

Join Our Innovative MediaLab Team as a Senior Data Engineer

Are you passionate about designing cutting-edge data solutions and eager to contribute to a dynamic, collaborative environment? We are seeking a seasoned Senior Data Engineer to join our Shared Services MediaLab team. In this role, you'll be at the forefront of building scalable, robust data infrastructures that power our strategic initiatives, from real-time analytics to advanced AI applications.

As a Senior Data Engineer, you will architect, develop, and maintain sophisticated data pipelines and infrastructure across cloud-native platforms such as Azure and AWS. You will work closely with data scientists, business analysts, IT teams, and stakeholders to deliver solutions that enable data-driven decision-making and support emerging AI and ML projects. Your expertise will help ensure our data environment is secure, scalable, and optimized for future growth.

What You'll Do

Data Architecture & Infrastructure
- Design and deploy enterprise-grade data architectures supporting structured, semi-structured, and unstructured data across multiple cloud platforms (Azure, AWS).
- Implement scalable data lakes and data warehouses optimized for both batch and real-time workloads.
- Develop and maintain data mesh architectures to facilitate self-service analytics while ensuring robust data governance and security.
- Architect cloud-native solutions utilizing serverless computing, containerization, and microservices.
Data Pipeline Development
- Build and orchestrate reliable, fault-tolerant data pipelines using modern ELT methodologies and tools like Apache Airflow, Azure Data Factory, and AWS Glue.
- Develop real-time streaming solutions with Apache Kafka, Apache Pulsar, and cloud-native services to support live data processing needs.
- Implement automated data quality frameworks with monitoring, alerting, and auto-remediation capabilities.
- Create CI/CD pipelines for data workflows, incorporating automated testing, deployment, and rollback procedures.
AI & Advanced Analytics Integration
- Embed machine learning workflows into data pipelines, enabling feature engineering, model training, and large-scale inference.
- Support MLOps practices with model versioning, A/B testing, and automated retraining pipelines.
- Build infrastructure to support generative AI initiatives, including vector databases and retrieval-augmented generation (RAG) systems.
- Collaborate with data scientists and developers to produce scalable ML models and ensure efficient inference.
Data Governance & Security
- Establish comprehensive data governance frameworks, including data lineage, metadata management, and cataloging.
- Ensure compliance with privacy laws (GDPR, CCPA) by implementing data masking, encryption, and strict access controls.
- Maintain audit trails for data processing activities and model predictions.
Performance & Monitoring
- Optimize data processing performance via query tuning, indexing, and resource management.
- Implement observability strategies, including metrics, logging, and distributed tracing for all data pipelines.
- Conduct root cause analyses and resolve data quality or system performance issues swiftly.
- Define and maintain SLAs for data freshness, accuracy, and system uptime.
Collaboration & Leadership
- Work closely with cross-functional teams to gather requirements and deliver impactful solutions.
- Provide technical mentorship to junior engineers and analysts.
- Lead technical design reviews and contribute to strategic technology planning.
- Document best practices, data architectures, and system workflows; lead knowledge-sharing initiatives.

Qualifications

Minimum of 7+ years of hands-on experience in data engineering, with a proven track record of building and maintaining large-scale production data systems.
Strong experience working directly with internal clients and stakeholders.
Extensive expertise in database development and management.
Bachelor's degree in Computer Science, Information Technology, or a related field (Master's preferred).
Proven experience in the following technical areas:
- Cloud platforms: Azure & AWS (data services, infrastructure management)
- Data frameworks: Apache Spark (PySpark, Scala, Java), Hadoop ecosystem, Databricks
- Real-time processing: Kafka, Pulsar, Kinesis, Event Hubs
- Data storage: SQL, NoSQL, NewSQL (PostgreSQL, MongoDB, Cassandra, Snowflake)
- Data modeling and warehousing: dimensional modeling, star/snowflake schemas, SCD
- ETL/ELT tools: Azure Data Factory, Fabric Dataflow, AWS Glue, dbt
- Infrastructure as Code: Terraform, Bicep, CloudFormation
- Containerization & Orchestration: Docker, Kubernetes
- Data lakehouse architectures: Delta Lake, Apache Iceberg, Apache Hudi
- MLOps tools and workflows: MLflow, Kubeflow, SageMaker
- Vector databases and embedding techniques for AI applications
- Observability tools: DataDog, Splunk, Prometheus, Grafana
- CI/CD pipelines: Azure DevOps, GitHub Actions, Jenkins
- Security best practices for cloud and data environments
Strong programming skills in Python, C#, and/or Scala.
Deep understanding of distributed systems, fault tolerance, and high-availability architectures.
Excellent problem-solving, communication, and collaboration skills.

Preferred Certifications & Additional Qualifications

Microsoft Certified: Azure Data Engineer Associate (DP-203)
Microsoft Certified: Fabric Data and Analytics Engineer
AWS Certified Data Engineer - Associate
Databricks Certified Data Engineer
SnowPro Advanced Data Engineer & Architect
Experience with graph databases, knowledge graphs, and compliance frameworks in data privacy.

What We Offer

Exciting opportunities to work on innovative AI-driven data projects.
Collaboration with a talented, motivated team of professionals.
Opportunities for professional growth and skills development.
A dynamic environment that encourages innovation and continuous learning.

Ready to shape the future of data at our company? Apply now and become a key driver of our data-driven success!

Note: This position is based in-office. Candidates must be authorized to work locally.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: bravo
Position Id: 43688
Posted 30+ days ago

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Senior Data Engineer (Developer)

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