Data Engineer - Databricks

Anchor Search Group Pte Ltd; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

The Anchor Search Group Pte Ltd is seeking a Data Engineer to design, build, and support reliable data ingestion and transformation pipelines on AWS and Databricks. You will work with architects, engineers, QA, and business teams to deliver production-ready data pipelines.

Responsibilities include batch and streaming data pipelines, Bronze/Silver/Gold data layers using PySpark and SQL, and implementing data quality, logging, and recovery while optimizing performance and cost.

Qualifications

• 3+ years of experience in data engineering or enterprise data-platform delivery.
• Hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
• Experience with Delta Lake and Bronze/Silver/Gold data layers.
• Proven ability to build production data pipelines with logging and recovery.
• Experience with AWS services (S3, IAM, Glue, Lambda, Kinesis).
• Strong understanding of data modelling, quality, and performance optimization.

Responsibilities

• Design and build batch and/or streaming pipelines using Databricks and AWS.
• Develop data processing across Bronze/Silver/Gold layers with Spark and SQL.
• Ingest data from APIs, files, databases, and object storage.
• Create reusable data-engineering components and datasets.
• Implement data validation, logging, error handling, and recovery.
• Optimize Spark jobs, clusters, and storage for cost and performance.
• Support CI/CD, SIT/UAT, production deployment and handover.
• Collaborate with platform, application, BI, and data-governance teams.

Skills

Data engineering

Databricks

Apache Spark

PySpark

SQL

Data modelling

Data quality

Performance optimization

Tools

Databricks

Delta Lake

AWS S3

AWS IAM

AWS Glue

AWS Lambda

AWS Kinesis

Job description

The Data Engineer will design, build, and support reliable data ingestion and transformation pipelines on AWS and Databricks. The role will work with architects, engineers, QA, and business teams to deliver data pipelines, curated datasets, data-quality controls, and production-ready operational processes.

Responsibilities:

• Design and build batch and/or streaming data pipelines using Databricks and AWS services.
• Develop data processing across Bronze, Silver, and Gold layers using SQL, Python / PySpark and Delta Lake.
• Implement ingestion from APIs, files, databases, object storage, or other enterprise data sources.
• Develop data transformations, dimensional or curated datasets, and reusable data-engineering components.
• Implement data validation, reconciliation, error handling, logging, rerun/recovery and monitoring.
• Optimize Spark jobs, clusters, partitioning, and storage for performance and cost.
• Support CI/CD, environment promotion, SIT/UAT, production deployment, documentation, and operational handover.
• Collaborate with platform, application, BI, and data-governance teams.

Mandatory Requirements:

• 3+ years of experience in data engineering or enterprise data-platform delivery.
• Hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
• Experience with Delta Lake and layered data architecture such as Bronze/Silver/Gold.
• Experience building production data pipelines with proper logging, error handling, and recovery.
• Experience with AWS services such as S3, IAM, Glue, Lambda, Kinesis, or related services.
• Good understanding of data modelling, data quality, and performance optimization.

Plus Points (Advantage)

• Databricks Workflows, Delta Live Tables, Unity Catalog, Auto Loader, or Structured Streaming.
• Experience with APIs, XML/JSON, event or near-real-time ingestion.
• CI/CD and infrastructure/configuration automation using Git-based tools.
• Experience with Tableau, BI datasets, or data warehouse integration.
• Databricks, AWS, data engineering, AI/ML, or GenAI-related certification(s).