Managing Consultant Data Engineering

We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data pipelines and data platforms. The ideal candidate should have strong experience with cloud data engineering, ELT/ETL frameworks, and modern data technologies, enabling the business to make data-driven decisions efficiently.

Responsibilities

• Design, develop, and maintain scalable data pipelines for batch and real-time processing.

• Build and optimize data lake, data warehouse, and data mart architectures.

• Develop and enhance ETL/ELT workflows using best practices.

• Work with large datasets, ensuring data quality, integrity, and governance.

• Collaborate with Data Scientists, Analysts, and Product teams to understand data needs.

• Implement data modeling (Star, Snowflake, 3NF) for analytics and reporting.

• Optimize database performance, query tuning, and data storage solutions.

• Ensure data security, access control, and compliance standards.

• Lead technical design discussions and mentor junior data engineers.

• Work with CI/CD pipelines, version control, and automation tools.

Requirements:

• Strong experience with cloud platforms: AWS / Azure / GCP.

• Hands-on experience in SQL, Python, and distributed data processing.

• Expertise in tools like Spark, Databricks, Hadoop, Hive, Airflow, Kafka or similar.

• Experience with data warehouses such as Snowflake, Redshift, BigQuery, or Synapse.

• Strong understanding of ETL/ELT, data modeling, and data architecture principles.

• Experience building real-time streaming pipelines (Kafka, Kinesis, EventHub).

• Proficiency with CI/CD, Git, DevOps workflows.

• Knowledge of data governance, security, and metadata management.