Deputy Head of Data Engineering
[December 1, 2023 ]
7,000,000 - 8,000,000 MMK
Full Time
Responsibility
- Develop and implement a data engineering strategy aligned with the overall data analytics strategy.
- Lead and manage a team of data engineers to deliver data engineering solutions that meet business needs, including hiring, mentoring, training, and performance management.
- Develop and maintain the data architecture, including data models, data pipelines, data storage, and data integration.
- Provide technical leadership and guidance to the data engineering team and work closely with other teams.
- Ensure the quality, accuracy, and completeness of data used for analytics.
- Evaluate and recommend new data engineering technologies, tools, and platforms.
- Foster a collaborative environment with other teams, such as data scientists and business analysts.
- Monitor and manage the performance of data engineering solutions, including identifying and addressing technical issues, optimizing performance, and ensuring scalability.
Requirement
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- At least 10 years of experience in data engineering, with at least 5 years of experience in a leadership role.
- Strong understanding of data engineering technologies and platforms, such as Hadoop, Spark, Kafka, and AWS.
- Experience with data modeling, ETL, data warehousing, and data integration.
- Excellent communication and collaboration skills, with the ability to work effectively with other teams and stakeholders.
- Experience with data lakes and distributed systems such as Hadoop and Spark, including knowledge of tools such as HDFS, YARN, and Hive.
- Strong experience with cloud-based data warehousing platforms, such as Amazon Redshift, Google BigQuery, or Snowflake.
- Experience with NoSQL databases such as MongoDB or Cassandra.
- Knowledge of containerization technologies such as Docker and Kubernetes.
- Familiarity with DevOps practices and tooling, including continuous integration and continuous delivery (CI/ CD).
- Knowledge of machine learning and AI technologies and their applications to data engineering.
- Strong understanding of data security and encryption methodologies, including knowledge of security protocols such as SSL/ TLS and OAuth.
- Experience with data streaming technologies such as Apache Kafka and Apache Flink.
- Familiarity with data virtualization and data federation technologies such as Denodo.
- Experience with data cataloging tools such as Alation, Collibra, or Informatica Axon.