Data Architect

Job Title: Data Architect – Data Integration & Engineering Location: Hybrid Experience: 8+ years Job Summary: We are seeking an experienced Data Architect specializing in data integration, data engineering, and hands-on coding to design, implement, and manage scalable and high-performance data solutions. The ideal candidate should have expertise in ETL/ELT, cloud data platforms, big data technologies, and enterprise data architecture. Key Responsibilities: 1. Data Architecture & Design: Develop enterprise-level data architecture solutions, ensuring scalability, performance, and reliability. Design data models (conceptual, logical, physical) for structured and unstructured data. Define and implement data integration frameworks using industry-standard tools. Ensure compliance with data governance, security, and regulatory policies (GDPR, HIPAA, etc.). 2. Data Integration & Engineering: Implement ETL/ELT pipelines using Informatica, Talend, Apache Nifi, or DBT. Work with batch and real-time data processing tools such as Apache Kafka, Kinesis, and Apache Flink. Integrate and optimize data lakes, data warehouses, and NoSQL databases. 3. Hands-on Coding & Development: Write efficient and scalable code in Python, Java, or Scala for data transformation and processing. Optimize SQL queries, stored procedures, and indexing strategies for performance tuning. Build and maintain Spark-based data processing solutions in Databricks and Cloudera ecosystems. Develop workflow automation using Apache Airflow, Prefect, or similar tools. 4. Cloud & Big Data Technologies: Work with cloud platforms such as AWS (Redshift, Glue), Azure (Data Factory, Synapse), and GCP (BigQuery, Dataflow). Manage big data processing using Cloudera, Hadoop, HBase, and Apache Spark. Deploy containerized data services using Kubernetes and Docker. Automate infrastructure using Terraform and CloudFormation. 5. Governance, Security & Compliance: Implement data security, masking, and encryption strategies. Define RBAC (Role-Based Access Control) and IAM policies for data access. Work on metadata management, data lineage, and cataloging. Required Skills & Technologies: Data Engineering & Integration: ETL/ELT Tools: Informatica, Talend, Apache Nifi, DBT Big Data Ecosystem: Cloudera, HBase, Apache Hadoop, Spark Data Streaming: Apache Kafka, AWS Kinesis, Apache Flink Data Warehouses: Snowflake, AWS Redshift, Google Big Query, Azure Synapse Databases: PostgreSQL, MySQL, MongoDB, Cassandra Programming & Scripting: Languages: Python, Java, Scala Scripting: Shell, PowerShell, Bash Frameworks: PySpark, SparkSQL Cloud & DevOps: Cloud Platforms: AWS, Azure, GCP Containerization & Orchestration: Kubernetes, Docker CI/CD Pipelines: Jenkins, GitHub Actions, Terraform, CloudFormation Security & Governance: Compliance Standards: GDPR, HIPAA, SOC 2 Data Cataloging: Collibra, Alation Access Controls: IAM, RBAC, ABAC Preferred Certifications: AWS Certified Data Analytics – Specialty Microsoft Certified: Azure Data Engineer Associate Google Professional Data Engineer Databricks Certified Data Engineer Associate/Professional Cloudera Certified Data Engineer Informatica Certified Professional Education & Experience: Bachelor's/Master’s degree in Computer Science/ MCA, Data Engineering, or a related field. 8+ years of experience in data architecture, integration, and engineering. Proven expertise in designing and implementing enterprise-scale data solutions. Show more Show less