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.
WHO YOU ARE:
You have a 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.
You are a highly driven professional and enjoy serving in a fast-paced, dynamic client-facing role where delivering solutions to exceed high expectations is a measure of success. You have a passion for leading teams and providing both formal and informal mentorship.
You have strong communication and interpersonal skills, and the ability to engage customers at a business level in addition to a technical level. You have a deep understanding of data governance and data privacy best practices.
You incorporate the usage of AI tooling, efficiencies, and code assistance tooling in your everyday workflows. You have a degree in Computer Science, Computer Engineering, Engineering, Mathematics, Management Information Systems or a related field of study.
The ideal candidate will have recent technical knowledge of the following:
• Programming languages (e.g. Python, Spark, Java, C++, Scala, etc.) • SQL and NoSQL databases (MySQL, DynamoDB, CosmosDB, Cassandra, MongoDB, etc.) • Data pipeline and workflow management tools (Airflow, Dagster, AWS Step Functions, Azure Data Factory, etc.) • Stream-processing systems (e.g. Storm, Spark-Streaming, Pulsar, Flink, etc.) • Data Warehouse design (Databricks, Snowflake, Delta Lake, Lake formation, Iceberg) • MLOps platforms (Sagemaker, Azure ML, Vertex.ai, MLFlow) • Container Orchestration (e.g. Kubernetes, Docker Swarm, etc.) • 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
Basic Qualifications:
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.