Job in UAE Dubai
|Hiring Organization||Emirates Airlines|
|Post Title||Job in UAE Dubai|
|Post Name||Senior Data Engineer|
|Qualification||Degree or honors (12+3 or equivalent) In a relevant field such as Computer Science, Computational Mathematics, Computer Engineering, or Software Engineering. Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence) a nice-to-have.|
|Employment Type||Full Time|
|Work Hours||8 Hours|
|Salary||AED 15000 To AED 20000 Per Month|
|Location||Dubai, United Arab Emirates 00000|
The Senior Data Engineer is a fully participating member of a cross-functional Enterprise Data & Analytics team working autonomously on technology development and problem resolution. The role involves the design, development, implementation, and maintenance of analytical solutions and products that support the Emirates Group businesses, using Big Data technologies and cloud-based data lake and data warehouse solutions.
- Lead technical design and build for small to medium-sized solutions in a team. Translate functional and non-functional data and analytics requirements into fit-for-purpose technical design. Ensure solution performance, business edge cases, and security-related issues are addressed while developing software.
- Debug issues of complexity, resolve blockers and follow design documents with minimal or no supervision.
- Complete data engineering coding tasks on problems of moderate to high scope and complexity. Demonstrate good coding principles. Conduct code reviews for peers. Ensure solutions adhere to published data privacy and cybersecurity principles.
- Operate with a data-driven mindset. Help translate data and analytics requirements into data solutions based on the approved technical designs. Assist with data analysis activities such as source system analysis, data modeling, data dictionary collection, data profiling, and source-to-target mapping to ensure solutions deliver on business needs.
- Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors. Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
- Work with senior and lead data engineers in the technical design process by contributing to the analysis of data application, data integration, large data storage, or data pipeline requirements.
- Update data inventories and registries as required to keep metadata and data lineage up-to-date, following agreed Data Governance standards, guidelines, and principles.
- Carry out unit testing independently. Troubleshoot issues, and fix defects that are of moderate to high complexity.
- Shadow senior and lead data engineers on design and architecture components, and collaborate with members of the cross-functional team to identify areas of inefficiency and propose solutions.
- Adhere to published coding standards, guidelines, and best practices and contribute to Data Engineering Playbooks and other data technology blueprints.
Qualifications & Experience
- Education: – Degree or honors (12+3 or equivalent) In a relevant field such as Computer Science, Computational Mathematics, Computer Engineering, or Software Engineering. Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence) a nice-to-have.
- Experience: – Minimum 2+ years of development, testing, and support experience in analytic applications such as Data Lake and Data Warehouse (preferably using the Big Data stack and Microsoft Azure cloud infrastructure) – 2+ years of Data Engineering (Fewer years’ experience will be considered for Masters degree holders)
- Experience with batch or real-time data ingestion; experience with coding pipelines that handle massive quantities of data (structured and unstructured), securely and in a timely fashion
- Understanding data architecture concepts such as data modeling, Big Data storage, Lambda architecture, data vault, and dimensional modeling nice-to-have
- Understanding of integration with source systems; able to load operational systems’ data into a single data platform using data integration tools
- Experience scheduling jobs that can be monitored efficiently and ensure data quality – Ability to conduct unit testing
- Strong SQL querying skills required
- Airline industry experiences nice-to-have Skills:
- Strong ability to conduct data analysis (e.g. source system identification, data dictionary/metadata collection, data profiling, source-to-target mapping) is preferred
- Operates with a “You Code It, You Own It” mindset (i.e. supports the products they build)
- Demonstrated problem-solver; able to design and document solutions independently
- Team player; able to collaborate with others to remove blockers, solve complex design problems and debug/resolve issues
- Able to deliver solutions (and associated value) interactively
- Is accountable and displays a positive attitude
- Self-starter and has a passion for exploring and learning new technologies, especially those in the Enterprise Data & Analytics space
- Key Technologies/Tools
- Big Data Hadoop, Spark, Scala, Hive, H-Base, Sqoop, Oozie, Apache Nifi, Airflow, HDFS, ADLS (Gen 2), Azure Data Factory (ADF), DataBricks, Kafka,
- Elasticsearch, AVRO / PARQUET file formats
- Data Analysis, Modelling, and Reporting
- Snowflake, SQL, Data Vault 2.0, MicroStrategy, Power BI
- Cloud Technologies
- Microsoft Azure and Cloudera technology stacks
- Integration and Messaging
- Streaming (e.g. Spark Streaming), SnapLogic, TIBCO, Kafka,
- GIT Bitbucket, Azure DevOps, Jenkins, JIRA, Confluence
- Java, Selenium, AppDynamics, HP Load Runner, Jmeter, Python, Automation Anywhere