Senior Data Engineer

Acumenz Consulting is seeking a Senior Data Engineer to design, develop, and optimize scalable data pipelines and analytics solutions on secure cloud platforms. The role involves collaborating with stakeholders and building cloud-native data solutions while leading technical discussions and mentoring teams.

Responsibilities:

• Design and deploy scalable, fault-tolerant data pipelines and ETL/ELT workflows
• Work with SQL, Python, PySpark, Spark, Kafka, Snowflake, Databricks, dbt, and Airflow
• Develop data ingestion, transformation, warehousing, and analytics solutions
• Apply modern data architectures including Data Vault, Star Schema, 3NF, and Medallion Architecture
• Build and optimize cloud-native data solutions using AWS
• Implement CI/CD, data governance, testing, monitoring, and performance optimization
• Collaborate with business and technical stakeholders to gather requirements and deliver solution architectures
• Support GenAI/AI-first development , including agents, embeddings, context retrieval, and AI workflows
• Integrate enterprise platforms such as Microsoft Graph, Salesforce, ServiceNow, Jira, and SharePoint
• Develop secure applications using Docker, Kubernetes, and CI/CD pipelines
• Lead technical discussions and mentor/support data engineering teams

Requirements:

• 5–8 years of relevant Data Engineering experience
• Expert in SQL, Python, PySpark, and data pipelines
• Strong experience with AWS services such as EMR, Glue, Athena, Lambda, EC2, DynamoDB, IAM, CloudWatch, and CloudFormation
• Experience with Spark, Kafka, Snowflake/Databricks, dbt, Airflow, and data streaming
• Knowledge of SQL/NoSQL databases, ETL, BI, Linux, networking, and CI/CD
• Experience with Agile/Jira and remote teams
• Strong communication, leadership, and stakeholder management skills
• AWS certification is a plus