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Senior Data Architecture Specialist

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Job Title: Data Engineering Team Lead

Job Summary:

We seek a seasoned Data Engineer to lead our Big Data team in delivering cutting-edge data solutions. As a technical leader, you will be responsible for developing architectures that meet the needs of clients and team members.

About this Role:

This role requires supporting the Data Engineering team in setting up the Data Lake on Cloud and implementing 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 NoSQL database, CI/CD and data delivery as per business requirements.

Key Responsibilities:

  • Build pipelines to bring in various 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.
  • Escalate critical issues to the Sponsor and/or Head of Data Engineering.
  • Ensure timelines (milestones, decisions, and delivery) are managed and value of initiative is achieved, without compromising quality.
  • Ensure final handover of initiative to business-as-usual processes, carry out a post-implementation review to ensure initiative objectives have been delivered.
Competencies & Personal Traits:
  • Team player with excellent problem analysis skills.
  • Proficient in Azure Databricks platform.
  • Experience with at least one Cloud Infra provider (Azure/AWS).
  • Experience in building data pipelines using batch processing with Apache Spark or Hive query language.
  • Knowledge of NOSQL databases and experience with Cosmos DB, Restful API's, and GraphQL.
  • 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 and NoSQL/document databases.