Senior Analyst jobs in United States, Florida, Miami

Technology – Data and Decision Science – Data Engineering – Senior

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.

Your key responsibilities

As a Senior Data Engineer, you will play a pivotal role in transforming data into actionable insights. Your time will be spent on various responsibilities, including:

• 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.

This role offers the opportunity to work with cutting-edge technologies and stay ahead of industry trends, ensuring you gain a competitive advantage in the market. The position may require regular travel to meet with external clients.

Skills and attributes for success

To thrive in this role, you will need a blend of technical and interpersonal skills. Your ability to communicate effectively and build relationships will be crucial. Here are some key attributes we look for:

• Strong analytical and decision-making skills.
• Proficiency in cloud computing and data architecture design.
• Experience in data integration and security.
• Ability to manage complex problem-solving scenarios.

To qualify for the role, you must have

• A Bachelor’s degree in Computer Science, Engineering, or a related field required (4-year degree). Master’s degree preferred
• 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.

Required Expertise for Senior Consulting Projects:

• 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.

Ideally, you’ll also have

• 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.

Data Modeler – Senior

We are seeking a highly skilled Senior Consultant Data Modeler with expertise in delivering data models that meet business requirements. 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 models and solutions that support the entire data asset lifecycle.

Your key responsibilities

As a Senior Data Modeler, you will play a pivotal role in transforming data into actionable insights. Your time will be spent on various responsibilities, including:

• Lead the design and development of conceptual, logical, and physical data models for the Enterprise Data Warehouse (EDW), adhering to Kimball dimensional methodology (dimensional modeling approach), a core skill for this role .
• Design and implement star schemas (Fact and Dimension tables) to support enterprise analytical, Business Intelligence (BI), and reporting requirements with high performance and query efficiency.
• Define and model Slowly Changing Dimensions (SCD) , with an emphasis on SCD Type 2 , to accurately capture and preserve the full historical context of dimension attributes (e.g., customer addresses, product categories) over time.
• Collaboratively determine the appropriate grain (atomic level of detail) for fact tables and identify measurable facts (metrics) and their relationships to the surrounding dimension tables.
• Design highly denormalized dimension structures to reduce joins and simplify querying for end-users and analytical tools.
• Collaborate with stakeholders and cross-functional teams to understand data requirements and design appropriate data models that align with business needs.
• Create and maintain data dictionaries and metadata repositories to ensure consistency and integrity of data models.
• Identify and resolve data model performance issues to optimize database performance and enhance overall system functionality.
• Manage and provide guidance to a small team of 1-3 resources
• Document and communicate data model designs and standards to ensure understanding and compliance across the organization.
• Create detailed source-to-target mapping (STM) documentation and data transformation specifications for ETL/ELT developers, including all SCD Type 2 logic and surrogate key generation rules.
• Stay current with industry best practices and trends in data modelling and incorporate new techniques and methodologies into our data modelling processes.
• Guide team on implementing data modelling techniques such as Kimball’s dimensional modeling
• Developing conceptual, logical, and physical data models to support data analysis and business intelligence.
• Utilize industry-standard data modeling tools (e.g., Erwin, PowerDesigner, ER/Studio) to create and maintain conceptual, logical, and physical models, and to manage version control.

To qualify for the role, you must have

• A Bachelor’s degree in STEM

• 7+ Years of hands-on Experience in data modelling
• Strong understanding of SQL and data modelling concepts such as Kimball dimensional modeling
• Experience working with major enterprise relational database platforms or cloud data warehouses (e.g., Oracle, SQL Server).
• Strong understanding of data warehousing principles, ETL/ELT architecture, data quality management, and metadata management.
• Mastery of SCD Type 2 (SCD2) implementation for preserving historical data (e.g., using surrogate keys , start/end dates, and current/active flags). Familiarity with other SCD types (Type 1, 3, 4, 6) is also expected
• The ability to analyze complex business processes and translate abstract business requirements into precise, efficient technical data models.
• Proficiency in data modelling tools such as Erwin / Visio or Power Designer
• Experience in designing and implementing database structures
• Ability to create and maintain conceptual, logical, and physical data models
• Knowledge of industry best practices for data modelling and database design
• Ability to collaborate with cross-functional teams to gather and analyze data requirements
• Experience in performance tuning and optimization of database queries
• Having cloud certification is an added advantage
• Strong analytical and problem-solving skills
• Excellent communication and documentation skills.
• Knowledge in Hospitality Domain is mandatory.

Ideally, you’ll also have

• Proven ability to navigate complex issues and make informed decisions
• Experience in supervising and guiding junior team members
• Demonstrated participation in sales opportunities and RFP responses

• Cloud knowledge and/or certification. Preferably Azure DP-203
• A passion for innovation and the strategic application of emerging technologies to solve real-world challenges.
• Spanish speaking
• Italian speaking