Architect, Data Engineering

Adelphi Group•Addison, TX

7d•$130,000 - $170,000•Hybrid

About The Position

Credera is a global consulting firm that combines transformational consulting capabilities, deep industry knowledge, AI and technology expertise to deliver valuable customer experiences and accelerated growth across various industries. We continuously evolve our services to meet the needs of future organizations and reflect modern best practices. Our unique global approach provides tailored solutions, transforming the most influential brands and organizations worldwide. Our employees, the lifeblood of our company, are passionate about making an extraordinary impact on our clients, colleagues, and communities. This passion drives how we spend our time, resources, and talents. Our commitment to our people and work has been recognized globally. As an Architect in Credera’s Data capability group, you will lead teams in implementing modern data architecture, data engineering pipelines, and advanced analytical solutions. Our projects range from designing and implementing the latest data platform approaches (i.e. Lakehouse, DataOps, Data Mesh) using best practices and cloud solutions, building scalable data and ML pipelines, democratizing data through modern governance approaches, and delivering data products using advanced machine learning, visualization, and integration approaches. You will act as the primary architect and technical lead on projects to scope and estimate work streams, architect and model technical solutions to meet business requirements, serve as a technical expert in client communications, and mentor junior project team members. On a typical day, you might expect to participate in design sessions, build data structures for an enterprise data lake or statistical models for a machine learning algorithm, coach junior resources, and manage technical backlogs and release management tools. Additionally, you will seek out new business development opportunities at existing and new clients.

Requirements

Minimum of 5 years of technical, hands-on experience building, optimizing, and implementing data pipelines and architecture
Experience leading teams to wrangle, explore, and analyze data to answer specific business questions and identify opportunities for improvement
Highly driven professional who enjoys serving in a fast-paced, dynamic client-facing role where delivering solutions to exceed high expectations is a measure of success
Passion for leading teams and providing both formal and informal mentorship
Strong communication and interpersonal skills, and the ability to engage customers at a business level in addition to a technical level
Deep understanding of data governance and data privacy best practices
Incorporates the usage of AI tooling, efficiencies, and code assistance tooling in everyday workflows
Degree in Computer Science, Computer Engineering, Engineering, Mathematics, Management Information Systems or a related field of study
Recent technical knowledge of programming languages (e.g. Python, Spark, Java, C++, Scala, etc.)
Recent technical knowledge of SQL and NoSQL databases (MySQL, DynamoDB, CosmosDB, Cassandra, MongoDB, etc.)
Recent technical knowledge of data pipeline and workflow management tools (Airflow, Dagster, AWS Step Functions, Azure Data Factory, etc.)
Recent technical knowledge of stream-processing systems (e.g. Storm, Spark-Streaming, Pulsar, Flink, etc.)
Recent technical knowledge of Data Warehouse design (Databricks, Snowflake, Delta Lake, Lake formation, Iceberg)
Recent technical knowledge of MLOps platforms (Sagemaker, Azure ML, Vertex.ai, MLFlow)
Recent technical knowledge of Container Orchestration (e.g. Kubernetes, Docker Swarm, etc.)
Recent technical knowledge of Metadata management tools (Collibra, Atlas, DataHub, etc.)
Experience with the data platform components on one or more of the following cloud service providers: AWS, Google Cloud Platform, Azure
Thrive in a fast-paced, dynamic, client-facing role where delivering solid work products to exceed high expectations is a measure of success
Contribute in a team-oriented environment
Prioritize multiple tasks in order to consistently meet deadlines
Creatively solve problems in an analytical environment
Adapt to new environments, people, technologies and processes
Excel in leadership, communication, and interpersonal skills
Establish strong work relationships with clients and team members
Generate ideas and understand different points of view
Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future; Credera will not sponsor applicants for U.S. work visa status for this opportunity

Responsibilities

Lead teams in implementing modern data architecture, data engineering pipelines, and advanced analytical solutions.
Design and implement the latest data platform approaches (i.e. Lakehouse, DataOps, Data Mesh) using best practices and cloud solutions.
Build scalable data and ML pipelines.
Democratize data through modern governance approaches.
Deliver data products using advanced machine learning, visualization, and integration approaches.
Act as the primary architect and technical lead on projects to scope and estimate work streams.
Architect and model technical solutions to meet business requirements.
Serve as a technical expert in client communications.
Mentor junior project team members.
Participate in design sessions.
Build data structures for an enterprise data lake or statistical models for a machine learning algorithm.
Coach junior resources.
Manage technical backlogs and release management tools.
Seek out new business development opportunities at existing and new clients.