- To Develop and maintain data ETL pipeline, builds the process of delivering. Use the external service API or make a SQL query, enrich the data and put it into centralized storage (data warehouse) or storage of unstructured data
- To Collaborate with Business users, Data source owners, Data Governance, MIS, BI to agree, align, and approve ETL process to ensure data accuracy, data quality, and business definition alignment.
- To Work with product engineering, operations, and executive team to understand data, structures, define information needs and develop prototype/solutions that supports desired business and technical capabilities.
- To utilize programming tools such as Spark/Python and other Hadoop ecosystem tools (e.g. Hive, Sqoop, Kafka, etc.) to bring together a diverse and massive set of data sources and making them easily accessible and useful for further
- To Collaborate closely with business SME’s, data scientists, executives to create dashboards, visualizations, statistical/machine learning models, transfer prototypes into large scale and efficient solutions.
- To Explore emerging technologies in Big Data, and analytics landscape for consideration and implementation.
- To Optimize, tune, and scale the Hadoop ecosystem to meet SLA requirements.
- To Perform troubleshooting and in-depth analysis of issues and provide clear, permanent solutions. Having a research mindset.
- To Be able to effectively work
independently/motivated; ability to handle multiple priorities.
- To Design database architecture (which requires database design knowledge) by using Customer Analytics Model provided by Customer Data Scientist
- Protects confidential information.
- Bachelor degree in Computer Science, Computer Engineering or a related fields.
- At least 3 years of experience in ETL/ ELT in Enterprise Big Data Scale.
- At least 2 years of experience in Big Data Stacks, Data Engineering or related field.
- Strong experience with Data Warehousing concepts and standards.
- Excellent with relational databases (SQL, MySQL, DB2, Oracle, etc.)
- Excellent with developer skills in Python, Scala, Java are highly desired.
- Excellent with Linux and shell scripting.
- Experience with non-relational databases (NoSQL, Hadoop, MongoDB, etc.)
- Experience with Spark, or the Hadoop ecosystem and similar frameworks.
- Experience with cloud platforms (AWS, Azure, Google)
- Understanding the basics of distributed systems
- Able to understand data models and business logic in a short span of time.
- Enjoy working as a team member as well as independently.
- Strong analytical and problem-solving skills.
- Good command of English both speaking and writing skills.
- Communication to team and management on project development, timelines, and results.
- Work closely with the other team members to meet business goals.
While technology is dtac's mode of operation, what makes dtac different is how it values its key asset – the people. In dtac, it is the belief shared throughout the company that people are the gear that drives business to its goal. The mentality is reflected through the way our culture is built around people and makes working at dtac an ever-challenging experience with opportunities to learn and create. That's why, every day, dtac is building up a strong force of people with diversified backgrounds and ideas, but with the same goal in mind, and creates one organization-wide team under the spirit of "One dtac"