Architect, Data Engineering

Job Summary

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.

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. Projects include designing and implementing the latest data platform approaches (Lakehouse, Data Ops, Data Mesh) using best practices and cloud solutions, building scalable data and ML pipelines, democratizing data through governance, and delivering data products with machine learning, visualization, and integration.

• Lead design and deployment of data platforms such as Lakehouse, Data Ops, and Data Mesh using cloud solutions.
• Build scalable data and ML pipelines; democratize data through governance.
• Serve as technical lead: scope, estimate work streams, architect and model technical solutions, and maintain client communication.
• Mentor junior team members; manage technical backlogs and release management tools.
• Identify and pursue new business development opportunities at existing and new clients.

• Minimum 5 years of hands‑on experience building, optimizing, and implementing data pipelines and architecture.
• Experience leading teams to wrangle, explore, and analyze data to answer business questions and identify improvement opportunities.
• Highly driven, thrive in fast‑paced client‑facing roles where exceeding expectations is key.
• Passionate about leading teams and providing formal and informal mentorship.
• Strong communication and interpersonal skills; able to engage customers at business and technical levels.
• Deep understanding of data governance and data privacy best practices.
• Incorporate AI tooling and code assistance in everyday workflows.
• Degree in Computer Science, Engineering, Mathematics, MIS, or related field.
• Recent technical knowledge of:
• Programming languages:
  Python, Spark, Java, C++, Scala.
• SQL and No
  
  SQL databases:
  MySQL, DynamoDB, CosmosDB, Cassandra, MongoDB.
• Data pipeline and workflow management tools:
  Airflow, Dagster, AWS Step Functions, Azure Data Factory.
• Stream‑processing systems:
  Storm, Spark‑Streaming, Pulsar, Flink.
• Data warehouse design:
  Databricks, Snowflake, Delta Lake, Lake Formation, Iceberg.
• MLOps platforms:
  Sage Maker, Azure ML, Vertex AI, MLFlow.
• Container orchestration:
  Kubernetes, Docker Swarm.
• Metadata management tools:
  Collibra, Atlas, Data Hub.
• Cloud providers: AWS, Google Cloud Platform, Azure.

• Thrive in fast‑paced client roles delivering solid work that exceeds expectations.
• Team‑oriented, prioritize multiple tasks to meet deadlines.
• Creatively solve problems in analytical environments.
• Adaptable to new environments, technologies, and processes.
• Excel in leadership, communication, and interpersonal skills.
• Establish strong work relationships with clients and team members.
• Generate ideas and value diverse perspectives.

Salary range: $130,000 – $170,000. The range is one component of the total compensation package for each unique employee.

• Health, mental health, vision, dental, and life insurance.
• Prescriptions, fertility and adoption benefits, community service days, paid parental leave, PTO, and 14 paid holidays.
• Matching 401(k), Healthcare & Dependent Flexible Spending Accounts, and disability benefits.

Employees can work remotely up to two days a week. Three days on‑site are expected, with flexibility to choose days and times that suit the project and team.

Typical travel ranges from 10% to 30% annually, with some projects requiring up to 80% for a period. Travel preferences are considered when assigning roles.

All qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity, sexual orientation, national origin, age, genetic information, veteran status, or disability. Applicants must be authorized to work in the U.S. without the need for employment‑based visa sponsorship now or in the future; this opportunity does not sponsor visas.