Data Engineering Lead (Pre-sales)

MAIN REQUIREMENTS:

• Data Engineering

• Pre-sales

RELATED WORK EXPERIENCE -

• Experience in data engineering, with at least 2-3 years in a leadership or senior technical role.

• Proven expertise in building and managing enterprise-level data pipelines and architectures.

• Strong experience with one or more cloud platforms (AWS, Azure, GCP).

DUTIES AND RESPONSIBILITIES:

• Lead and mentor a team of data engineers, fostering collaboration, innovation, and continuous improvement.

• Define and enforce data engineering standards, coding practices, and architectural guidelines.

• Partner with data scientists, analysts, and business stakeholders to translate requirements into scalable solutions.

• Design and maintain high-performance ETL/ELT pipelines and workflows.

• Build and optimize data lake, data warehouse, and streaming data solutions.

• Ensure systems support structured, semi-structured, and unstructured data sources.

• Develop data transformation and preparation processes to deliver clean, reliable, analytics-ready datasets.

• Implement validation, anomaly detection, and automated quality checks to ensure accuracy and consistency.

• Define and execute data remediation strategies to resolve issues with minimal business disruption.

• Implement and manage cloud-based data platforms (AWS, Azure, or GCP).

• Apply modern frameworks (e.g., Spark, Kafka, Airflow, DBT) for efficient data processing.

• Oversee data modeling, schema design, and database optimization (SQL/NoSQL).

• Ensure accuracy, consistency, and availability of data across platforms.

• Implement governance, lineage, validation frameworks, and security best practices.

• Monitor, troubleshoot, and optimize pipelines to meet SLAs and performance benchmarks.

• Stay current with emerging data engineering and analytics technologies.

• Recommend improvements to systems, tools, and processes to enhance scalability, reliability, and quality.

• Other job-related activities that may be assigned from time to time.