Job Description


  • 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 (data lakes).
  • 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 analysis.
  • 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.

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