Data Engineer

BLAZECORP PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading data technology company in Singapore is seeking a Data Engineer to support the Data Engineering team in building a Data Lake on Cloud. The role requires expertise in data pipelines, Databricks, and NoSQL databases along with 5+ years of experience in cloud platforms and big data environments. Candidates with relevant Data and Analytics certifications are preferred. This role offers a dynamic work environment with a strong focus on collaboration.

Qualifications

• 5+ years of experience in Enterprise IT applications in cloud and big data environments.
• Certifications related to Data and Analytics are a plus.

Responsibilities

• Build pipelines from multiple sources including social media.
• Collaborate with teams to source data.
• Provide effective solution design based on business needs.
• Manage timelines and quality across projects.
• Escalate risks and critical issues to relevant stakeholders.
• Conduct post-implementation reviews.
• Execute coordinated communications for delivery.
• Conduct post-implementation reviews to capture lessons.

Skills

Expertise in Databricks

Experience with Cloud Infra providers (Azure/AWS)

Data pipelines using Apache Spark

Streaming data pipeline with Apache Spark

Knowledge of NoSQL databases

Expertise in Cosmos DB

Knowledge of ETL processing tools

Scripting (shell / bash)

Working with multiple data sources

CI/CD tools

Understanding of DevOps practices using Git

Problem analysis skills

Job description

Data Engineer - JD

As Data Engineer, you will support the Data Engineering team in setting up the Data Lake on Cloud and the implementation of a 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.

Job Responsibilities

• 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.

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 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.