ETL Azure

 Support the development of the organizational Data Strategy and support data management in line with strategic business objectives and FAB cultures and values.
 Supports the Data Engineering Lead/Operations in the development and oversight of the big data platform, standards, practices, policies and processes.
 Supports the development of the Data Engineering Office as a center of excellence committed to ingraining a data-driven decision making culture across the organization, teaming with external partners, and offering end-to-end data services across business and support groups.
 Aligns architecture with business requirements.
 Promotes good data engineering practices and the management of data as a strategic asset.

Core responsibilities

 Provide L2, L3 Support for Analytics platform issues.
 Debug day-to-day job issues in Analytics platform and provide solutions.
 Maintain service uptime & SLA as committed.
 Perform Tuning and increase Operational efficiency on a continuous basis.

KNOWLEDGE, SKILLS, & EXPERIENCE:

Minimum Qualifications:
 Degree educated with a minimum of 4 years of direct experience, 5+ years overall industry experience
Minimum Experience:
 Minimum 4 years of work experience in Data warehousing technologies and minimum 2 years of work experience in Big Data or Hadoop platform environment (Spark, HBase, HDFS, Hive, Parquet, Sentry, Impala and Sqoop).
 Good experience in Level 2, 3 support for performing hot fixes and dealing with platform issues in production environment.
 Good knowledge in ETL Architecture and Hadoop platform architecture.
 Require good Unix skills and good knowledge about Linux networks etc.
 Experience in tool Integration, automation, configuration management in GIT, Jira platforms.
 Should be proficient in writing shell scripts, automating batch and designing scheduler processes.
 Should be able to understand Python/Scala/Java programs and debug the issues.
 Require good understanding and knowledge about Informatica BDM/BDS/CDC, Hadoop Ecosystem, HDFS and Big Data concepts.
 Good understanding of Software Development Life Cycle (SDLC), agile methodology.
 Excellent oral, written communication and presentation skills, analytical and problem solving skills.
 Self-driven, Ability to work independently and as part of a team.

Knowledge, Skills, and Attributes:
Knowledge and Skills
 Good knowledge of Big Data platforms, frameworks, policies, and procedures and Informatica product as well.
 Proficient understanding of distributed computing principles
 Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala
 Good knowledge of Informatica tools, such as PowerExchange, BDM/BDS, EDC/EDQ/Axon and CDC
 Experience with Cloudera, NoSQL databases, such as HBase, Big Data.
 Experience with building stream-processing systems, using solutions such as Spark-Streaming and ideally Kafka.
 Excellent SQL knowledge.
 Experience on Cloud big data technologies beneficial, like AWS and Azure.
 Kafka experience highly beneficial.

Attributes
 A reliable and trustworthy person, able to anticipate and deal with the varying needs and concerns of numerous stakeholders adapting personal style accordingly.
 Adaptable and knowledgeable who is able to learn and improve his skills with existing and new technologies