Lead Data Architect

IBRSuitland, MD
Onsite

About The Position

At Imagine Believe Realize, LLC we are driven by innovation, transformation and a relentless pursuit of excellence. As an industry leader delivering impactful results, we thrive on solving complex technical challenges and developing cutting-edge solutions that empower our customers and advance critical missions. IBR is a fast-growing company fueled by passion, curiosity, and innovative thinking – where every team member has the opportunity to continuously learn, unlock their full potential, and redefine what is possible in engineering and technology. If you are inspired by innovation, eager to make a difference, and ready to bring your creativity and expertise to a mission-focused team, we invite you to join us and together, we will shape the future. Let’s Make It Real!

Requirements

  • 14+ years of IT experience focusing on enterprise data architecture and management
  • Must be able to obtain and maintain a Public Trust security clearance
  • Bachelor’s degree required
  • Experience in Conceptual/Logical/Physical Data Modeling to define how data is stored, processed, and accessed.
  • Expertise in Relational and Dimensional Data Modeling OLTP and OLAP workloads noSQL Databases Time-Series Databases Graph Databases
  • Strong experience with data extraction, cleaning, and transformation (ETL) processes.
  • Expertise in statistical modeling, machine learning algorithms, and data mining techniques.
  • Experience with Data processing frameworks, Orchestration, Structured Streaming, Data and Delta Lake concepts, and Delta Live Tables.
  • Expertise in Spark/Python/Databricks, Data Lake and SQL
  • Experience leading and architecting enterprise-wide initiatives specifically system integration, data migration, transformation, data warehouse build, data mart build, and data lake implementation / support.
  • Advanced level understanding of streaming data pipelines and how they differ from batch systems
  • Formalize concepts of how to handle late data, defining windows, and data freshness
  • Advanced understanding of ETL and ELT and ETL/ELT tools such as SSIS, Pentaho, Data Migration Service etc.
  • Understanding of concepts and implementation strategies for different incremental data loads such as tumbling window, sliding window, high watermark, etc.
  • Familiarity and/or expertise with Great Expectations or other data quality/data validation frameworks
  • Understanding of streaming data pipelines and batch systems
  • Familiarity with concepts such as late data, defining windows, and how window definitions impact data freshness
  • Experience with data lineage (technical, business, operational) and observability
  • Experience developing open archive solutions based using Parquet.
  • Advanced level SQL experience (Joins, Aggregation, Windowing functions, Common Table Expressions, RDBMS schema design, Postgres performance optimization, and caching)
  • Indexing and partitioning strategy experience.
  • Experience with large-scale, high-performance enterprise big data application deployment and solutioning.
  • Understanding how to create DAGs to define workflows
  • Experience working with JSON and defining JSON Schemas
  • Experience setting up and management Confluent/Kafka topics and ensuring performance using Kafka
  • Familiarity with Schema Registry, message formats and data storage options such as Avro, ORC, Parquet etc.
  • Table Formats and Lakehouse technologies experience utilizing Apache Iceberg (schema evolution, large-scale analytics, and ACID), Delta Lakes, and Apache Hudi
  • Understanding how to manage ksqlDB SQL files and migrations and Kafka Streams
  • Experience with incremental ingestion of data using Batch Ingestion Patterns, Streaming & Event-Driven Architecture, Change Data Capture (CDC), and API-Based Integration.
  • Experience with data governance, security, compliance, metadata management, and data cataloging.
  • Ability to thrive in a team-based environment
  • Experience briefing the benefits and constraints of technology solutions to technology partners, stakeholders, team members, and senior level of management

Nice To Haves

  • Familiarity with CI/CD pipelines, containerization, and pipeline orchestration tools such as Airflow, Prefect, etc., but not required.
  • Architecture experience in AWS environment a bonus
  • Familiarity working with Kinesis and/or Lambda specifically with how to push and pull data, how to use AWS tools to view data in Kinesis streams, and for processing massive data at scale a bonus
  • Experience with Docker, Jenkins/GitLab, and CloudWatch
  • Ability to write and maintain Jenkins files for supporting CI/CD pipelines
  • Experience working with AWS Lambdas for configuration and optimization
  • Experience working with DynamoDB to query and write data
  • Experience with S3
  • Knowledge of Python (Python 3 desired) for CI/CD pipelines a bonus
  • Familiarity with Pytest and Unittest a bonus

Responsibilities

  • Develop conceptual, logical, and physical data models to define how data is stored, processed, and accessed.
  • Identify the strategy, tooling, and governance for implementing a common Enterprise Metadata Repository.
  • Create and maintain database architectures in alignment with business requirements, ensuring integrity, scalability, and performance.
  • Design solutions to integrate data from multiple internal and external sources, enabling a unified view for business use.
  • Establish policies, procedures, and standards for data quality, security, and regulatory compliance.
  • Implement measures to protect sensitive data from unauthorized access and ensure regulatory compliance.
  • Work closely with data engineers, analysts, scientists, and business stakeholders to ensure data solutions meet organizational needs.
  • Oversee migration from legacy systems, optimize existing data systems, and monitor performance, leveraging automation where possible.
  • Prepare architecture reports and maintain documentation for management and technical teams.
  • Collaborate with software developers, system architects, and business analysts to develop, verify, and optimize data science solutions, including AI/ML-based ones.
  • Lead and mentor a team of data scientists and data engineers, providing technical guidance and support.

Benefits

  • Nationwide medical, dental, and vision insurance
  • 3 weeks of Paid Time Off and 11 Paid Federal Holidays
  • 401k matching
  • Life Insurance, Short-Term Disability, and Long-Term Disability at no cost to our employees
  • Supplemental insurance options
  • Flexible spending accounts and Dependent Care spending accounts
  • Wellness incentives
  • Reimbursement for professional development and certifications
  • Access to training assistance opportunities to support career growth and progression
  • Hybrid and Remote work opportunities to support work-life balance
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