Data Engineering Lead Job Opportunity at Lifelancer

Responsibilities

Data Architecture and Design: Design and implement scalable and efficient data architectures to support the organization's data processing needs. Work closely with cross-functional teams to understand data requirements and ensure that data solutions align with business objectives.

ETL Development: Oversee the development of robust ETL processes to extract, transform, and load data from various sources into the data warehouse. Ensure data quality and integrity throughout the ETL process, implementing best practices for data cleansing and validation.

Big Data Technologies: Stay abreast of emerging trends and technologies in big data and analytics, and assess their applicability to the organization's data strategy. Implement and optimize big data technologies to process and analyze large datasets efficiently.

Cloud Integration: Collaborate with the IT infrastructure team to integrate data engineering solutions with cloud platforms, ensuring scalability, security, and performance.

Performance Monitoring and Optimization: Implement monitoring tools and processes to track the performance of data pipelines and proactively address any issues. Optimize data processing workflows for improved efficiency and resource utilization.

Documentation: Maintain comprehensive documentation for data engineering processes, data models, and system architecture. Ensure that team members follow documentation standards and best practices.

Collaboration and Communication: Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and deliver solutions that meet those requirements. Communicate effectively with technical and non-technical stakeholders, providing updates on project status, challenges, and opportunities.

Qualifications

Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.

6-8 years of professional experience in data engineering.

In-depth knowledge of data modeling, ETL processes, and data warehousing.

Expertise in building data warehouses using Snowflake.

Experience in data ingestion, data lakes, data mesh, and data governance.

Proficiency in Python programming.

Strong understanding of big data technologies and frameworks such as Hadoop, Spark, and Kafka.

Experience with cloud platforms like AWS, Azure, or Google Cloud.

Familiarity with database systems including SQL, NoSQL, and data pipeline orchestration tools.

Excellent problem-solving and analytical skills.

Strong communication and interpersonal skills.

Proven ability to work collaboratively in a fast-paced, dynamic environment.

Apply Now

Please apply on the Lifelancer platform at the following link for screening steps and a quicker response: