Data Engineer

Job Summary:

Using architectures and data engineering techniques to design and provide tools dedicated to data extraction, analysis and enhancement. Help define, implement, and ship significant, innovative improvements to the data infrastructure to further Synergys Enterprise data goals.

Qualification:

Master''s / Bachelor''s degree in Computer Science, Computer Application, Information Systems or equivalent.

ExperienceRequired:

• Strong experience (7+ years) writing complex SQL / NoSQL statements and ETL processes.
• Experience (5+ years) on Big Data technologies such as Hadoop, Spark, ElasticSearch
• Proven experience (5+ years) in data engineering in complex environments (e.g. multitenant architecture, Cloud)
• Proven experience (3+ years) on innovation implementation from exploration to production: these may include containerization (i.e. Docker/Kubernetes), Big data (Hadoop, Spark), on premise and cloud (Azure, AWS, Google)
• Deep understanding of E2E software development in a team, and a track record of shipping software on time
• Experience consuming enterprise web-services (REST, JSON/XML, MySQL/PostgreSQL) and expose own services to help design the next generation of back-end APIs and functionality.
• Aptitude with ETL concepts and tools, including experience ingesting, processing, and transforming a variety of data at scale.

• Proficiency with SQL and NoSQL databases, data warehousing concepts, and cloud-based analytics database (e.g. Snowflake , Databricks or Redshift) administration

Skills Required:

• Problem Solver
• Positive Attitude
• Resilience
• Commitment & Accountability
• Learnability and Adaptability

Roles & Responsibilities

1.Ensure that the team designs, develops, and delivers high-quality, performant, scalable, well-tested, documented, and sensible technical solutions.

2.Contribute to build & maintain the global analytic environment to ease exploitation of data.

3. Contribute to build data engineering pipelines & API for Data Science / Big Data applications, take active part in data architecture conception, environments design, core components development based on conceptual architecture.

4. Act as a SME and tech lead / veteran for any data engineering question and manage data engineers within the Data and Analytics department.

5. Promote services, contribute to the identification of innovative initiatives within the Group, share information on new technologies in dedicated internal communities.

6. Ensure compliance with policies related to Data Management and Data Protection.