Data Engineer - JD

Job Description & Requirements: -

As Data Engineer, you will support Data Engineering team in setting up the Data Lake on Cloud and the implementation of standardized Data Model, single view of customer.

You will develop data pipelines for new sources, data transformations within the Data Lake , implementing GRAPHQL, work on no sql database, CI/CD and data delivery as per the business requirements.

Job Description:

•

Build pipelines to bring in a wide variety of data from multiple sources within the organization as well as from social media and public data sources.

•

Collaborate with cross functional teams to source data and make it available for downstream consumption.

•

Work with the team to provide an effective solution design to meet business needs.

•

Ensure regular communication with key stakeholders, understand any key concerns in how the initiative is being delivered or any risks/issues that have either not yet been identified or are not being progressed.

•

Ensure dependencies and challenges (risks) are escalated and managed. Escalate critical issues to the Sponsor and/or Head of Data Engineering team.

•

Ensure timelines (milestones, decisions and delivery) are managed and achieved, without compromising quality and within budget.

•

Ensure an appropriate and coordinated communications plan is in place for initiative execution and delivery, both internal and external.

•

Ensure final handover of initiative to business-as-usual processes, carry out a post implementation review (as necessary) to ensure initiative objectives have been delivered, and any lessons learnt are included in future processes.

•

Who we are looking for:

Competencies & Personal Traits: -

•

Expertise in Databricks

•

Experience with at least one Cloud Infra provider (Azure/AWS)

•

Experience in building data pipelines using batch processing with Apache Spark (Spark SQL, Dataframe API) or Hive query language (HQL)

•

Experience in building streaming data pipeline using Apache Spark Structured Streaming or Apache Flink on Kafka & Data Lake

•

Knowledge of NOSQL databases.

•

Expertise in Cosmos DB, Restful APIs and GraphQL

•

Knowledge of Big data ETL processing tools, Data modelling and Data mapping.

•

Experience with Hive and Hadoop file formats (Avro / Parquet / ORC)

•

Basic knowledge of scripting (shell / bash)

•

Experience of working with multiple data sources including relational databases (SQL Server / Oracle / DB2 / Netezza), NoSQL / document databases, flat files

•

Experience with CI CD tools such as Jenkins, JIRA, Bitbucket, Artifactory, Bamboo and Azure Dev-ops.

•

Basic understanding of DevOps practices using Git version control

•

Ability to debug, fine tune and optimize large scale data processing jobs

•

Excellent problem analysis skills

•

Working Experience

•

5+ years (no upper limit) of experience working with Enterprise IT applications in cloud platform and big data environments.

Professional Qualifications

Certifications related to Data and Analytics would be an added advantage