Databricks Data Engineer - Senior - Consulting - Location OPEN

EY•Hartford, DC

1d•$106,900 - $200,600•Hybrid

About The Position

We are seeking a highly skilled Senior Consultant Data Engineer with expertise in cloud data engineering, specifically Databricks. The ideal candidate will have strong client management and communication skills, along with a proven track record of successful end-to-end implementations in data engineering projects. In this role, you will design and build analytics solutions that deliver significant business value. You will collaborate with other data and analytics professionals, management, and stakeholders to ensure that technical requirements align with business needs. Your responsibilities will include creating scalable data architecture and modeling solutions that support the entire data asset lifecycle.

Requirements

A Bachelor’s degree in Computer Science, Engineering, or a related field required (4-year degree).
Typically, no less than 2 - 4 years relevant experience in data engineering, with a focus on cloud data solutions.
5+ years of experience in data engineering, with a focus on cloud data solutions.
Expertise in Databricks and experience with Spark for big data processing.
Proven experience in at least two end-to-end data engineering implementations, including: Implementation of a data lake solution using Databricks, integrating various data sources, and enabling analytics for business intelligence. Development of a real-time data processing pipeline using Databricks and cloud services, delivering insights for operational decision-making.
Strong programming skills in languages such as Python, Scala, or SQL.
Experience with data modeling, ETL processes, and data warehousing concepts.
Excellent problem-solving skills and the ability to work independently and as part of a team.
Strong communication and interpersonal skills, with a focus on client management.
Strategic Thinking: Ability to align data engineering solutions with business strategies and objectives.
Project Management: Experience in managing multiple projects simultaneously, ensuring timely delivery and adherence to project scope.
Stakeholder Engagement: Proficiency in engaging with various stakeholders, including executives, to understand their needs and present solutions effectively.
Change Management: Skills in guiding clients through change processes related to data transformation and technology adoption.
Risk Management: Ability to identify potential risks in data projects and develop mitigation strategies.
Technical Leadership: Experience in leading technical discussions and making architectural decisions that impact project outcomes.
Documentation and Reporting: Proficiency in creating comprehensive documentation and reports to communicate project progress and outcomes to clients.

Nice To Haves

Master’s degree preferred
Experience with data quality management.
Familiarity with semantic layers in data architecture.
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
Knowledge of data governance and compliance standards.
Experience with machine learning frameworks and tools.

Responsibilities

Designing, building, and operating scalable on-premises or cloud data architecture.
Analyzing business requirements and translating them into technical specifications.
Optimizing data flows for target data platform designs.
Design, develop, and implement data engineering solutions using Databricks on cloud platforms (e.g., AWS, Azure, GCP).
Collaborate with clients to understand their data needs and provide tailored solutions that meet their business objectives.
Lead end-to-end data pipeline development, including data ingestion, transformation, and storage.
Ensure data quality, integrity, and security throughout the data lifecycle.
Provide technical guidance and mentorship to junior data engineers and team members.
Communicate effectively with stakeholders, including technical and non-technical audiences, to convey complex data concepts.
Manage client relationships and expectations, ensuring high levels of satisfaction and engagement.
Stay updated with the latest trends and technologies in data engineering and cloud computing.