Lead Data Engineer
We are seeking a highly skilled and experienced Lead Data Engineer to design, develop, and lead the implementation of scalable data pipelines and cloud-based data infrastructure. The ideal candidate will have a strong background in data engineering, cloud technologies, and team leadership. Cloud certification (e.g., AWS, Azure, GCP) is required to demonstrate expertise in modern cloud environments.
Department:
BI & Data Services
Employment Type:
Full-time
Experience:
7+ Years
Workplace Type:
On-site
Number of Vacancies:
1
Location:
Dhaka
Deadline:
15 March 2026
Key Responsibilities
- Lead the design, development and maintenance of scalable data pipelines and ETL/ELT workflows.
- Design and implement data models, data warehouses, and data lakes using cloud-native solutions.
- Lead a team of data engineers in developing data pipelines using technologies such as Apache airflows, Kafka, big query and GCP services.
- Collaborate with cross-functional teams to understand data requirements and provide data solutions that meet business needs.
- Establish best practices for data management, including data governance, quality, and security.
- Mentor junior engineers and foster a culture of continuous learning and improvement within the team.
- Evaluate and integrate new data technologies and tools to enhance our data capabilities.
- Overseeing data security and compliance measures.
- Evaluating and recommending new technologies to enhance data infrastructure.
- Providing technical expertise and guidance for critical data projects.
Required Skills & Experience
Experience Requirements
- BSc or MSc in computer science, engineering, or a related field.
- 7+ years of experience in data engineering or related fields, with a proven track record of leading data projects.
Technical Skills
- Deep understanding of data modeling, data warehousing, and modern data architecture (e.g. Big query, Lakehouse, Delta Lake).
- Expertise in ETL tools (Airflow, DBT, Informatica, etc.) and data integration.
- Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
- Strong organizational skills with the ability to manage projects and priorities effectively.
- Ability in defining project estimation.
- Hands-on experience with big data technologies such as Hadoop, Spark, or similar.
- Experience with cloud data platforms (e.g., AWS, Google Cloud, Azure) and data warehousing solutions (e.g., BigQuery, Snowflake, Redshift).
- Experience with multiple database technologies, especially distributed columnar databases and Time Series.
- Excellent problem-solving skills and the ability to troubleshoot complex data issues.
- Experience with real-time data streaming technologies (Kafka, Pub/Sub, RabbitMQ).
- Familiarity with containerization and orchestration tools (Docker, Kubernetes).
- Demonstrated leadership abilities, with experience guiding and mentoring team members.
- A collaborative mindset and a commitment to fostering a positive team culture.
- Adaptability to thrive in a fast-paced, evolving environment.
Preferred Qualifications
- Cloud certification required (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate, Google Cloud Professional Data Engineer).
- Hands on experience on BigQuery, Apache Airflow, and Kafka.
- Experience with machine learning frameworks and concepts.
Interview Steps
- Technical/Functional Interview (on-site)
- HR Interview (online)
- Offer