- Company Name
- Response Informatics
- Job Title
- Data Architect
- Job Description
-
Job Title: Data Architect
Role Summary:
Design, develop, and maintain scalable, cloud‑based data platforms that support analytics, AI, and data engineering workflows. Lead end‑to‑end data pipeline creation, ELT processes, and data warehousing or lakehouse architecture, ensuring high availability, performance, and governance across multi‑cloud environments.
Expectations:
- Minimum 13 years in IT with proven expertise as a Data Engineer or Data Architect.
- Advanced knowledge of cloud‑native, open‑source data platforms and analytics tools.
- Demonstrated ability to implement AI‑powered assistants and modern ELT pipelines.
- Proficiency in SQL, relational databases, and code‑based transformation tools (dbt, Spark, Trino).
- Strong background in Python, orchestration (Airflow, Dagster, Luigi), event streaming (Kafka, RabbitMQ), and storage formats (Iceberg, Delta Lake).
- Experience with containerization (Kubernetes, Docker/Podman) and data modeling for OLAP and mining.
- Excellent written and spoken English.
Key Responsibilities:
- Architect and optimize data warehouse/lakehouse solutions on cloud platforms.
- Build and automate ELT pipelines using dbt, Spark, Trino, and orchestration tools.
- Integrate AI assistants (e.g., Amazon Q) to streamline data engineering tasks.
- Design data models, schema, and metadata governance for analytical workloads.
- Configure and manage event streams and message brokers for real‑time data ingestion.
- Implement storage protocols (Iceberg, Delta Lake) and ensure data integrity.
- Deploy and manage containerized services with Kubernetes and Docker/Podman.
- Collaborate with data science, analytics, and DevOps teams to meet business requirements.
- Ensure compliance with data security, privacy, and regulatory standards.
Required Skills:
- Cloud computing (AWS, GCP, Azure) – data platform services.
- SQL, dbt, Spark, Trino, Python programming.
- Orchestration: Airflow, Dagster, Luigi.
- Event streaming: Kafka, RabbitMQ.
- Storage formats: Apache Iceberg, Delta Lake.
- Containerization: Kubernetes, Docker/Podman.
- Data modeling, OLAP, data mining tools.
- AI‑powered assistant integration.
- Strong analytical, problem‑solving, and communication skills.
- English fluency (reading/writing/speaking).
Required Education & Certifications:
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
- Professional certifications in cloud architecture (e.g., AWS Certified Solutions Architect, GCP Professional Data Engineer) preferred.
- Certifications in data engineering or big data platforms (e.g., Databricks, Cloudera) are a plus.