Data Engineer II

27Global•Leawood, KS

6h•Hybrid

About The Position

As a Data Engineer II, you’ll be responsible for contributing to the design and development of enterprise data solutions that support analytics, business intelligence, and scalable applications. You’ll work closely with data and software architects, consultants and other engineers to deliver data models, integration strategies, and governance practices that empower client’s data-driven decisions. Joining 27Global as a Consultant is an exciting, high-growth opportunity offering a competitive base salary, performance bonuses, and variable compensation incentives.

Requirements

BA/BS/Master’s degree in Computer Science, Information Systems, Data Science, or related field
2 - 4 years of experience in data architecture, data engineering, or related roles delivering scalable architecture solutions from design to production
2 - 4 years of experience writing .Net code or other OOP languages in an Agile environment
Demonstrated leadership skills with the ability to collaborate with and lead on-shore and off-shore team members
Proficient technical skills in: Spark, Scala, C#, PySpark, Data Lake, Delta Lake, Relational and NoSQL Databases, AWS Glue and Azure Synapse
Experience with SQL, ETL/ELT, and data modeling
Experience with cloud platforms (AWS, Azure, GCP) and implementing modern data platforms with data lake
Knowledge of data governance, security, and compliance frameworks
Ability to context switch and work on a variety of projects over specified periods of time
Ability to work at the 27Global office in Leawood, KS with hybrid work flexibility after 90 days, and occasionally onsite at client offices
Flexibility to occasionally travel to client sites may be required, typically 1 week per quarter or less
Legal authorization to work in the United States and the ability to prove eligibility at the time of hire

Nice To Haves

Certifications: AWS Solution Architect, Azure Data Engineer, Databricks Data Engineer
Hands-on experience with Databricks for building and optimizing scalable data pipelines, Delta Lake, and Spark-based analytics
Hands-on experience with big data tools (Spark, Kafka)
Modern data warehouses (Snowflake, Redshift, BigQuery)
Familiarity with machine learning pipelines and real-time analytics
Strong communication skills and ability to influence stakeholders
Prior experience implementing enterprise data governance frameworks
Experience in a client-facing role, working directly with clients from multiple levels of the organization; often presenting and documenting client environment suggestions and improvements

Responsibilities

Participate in the design and implementation of scalable, secure, and high-performance data architectures.
Develop and maintain conceptual, logical, and physical data models.
Work closely with architects to define standards for data integration, quality, and governance.
Collaborate with engineers, analysts, and business stakeholders to align data solutions with organizational needs.
Support cloud-based data strategies including data warehousing, pipelines, and real-time processing.
Design and optimize data pipelines that support AI, machine learning, and advanced analytics workloads.
Implement data preprocessing, feature engineering, and real-time inference capabilities for predictive modeling.
Integrate AI/ML models into production environments using tools such as AWS SageMaker, Azure Machine Learning, or Databricks.
Assess, learn, and apply emerging data technologies and frameworks to enhance solutions and stay current with industry trends.