Senior Data Engineer - A26408

Activate Interactive Pte Ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Flexible work arrangement

Learning & development budget (SHRI 25

Job summary

Activate Interactive Pte Ltd is seeking a Senior Data Engineer in Singapore to design, build, productionise and operate trusted data pipelines on the SWDA platform using AWS and Databricks. You will provide technical leadership across ingestion, transformation, quality, lineage and orchestration to support analytics, reporting and ML workloads.

You will lead data pipeline architecture, lakehouse patterns, and data product engineering across batch and streaming data, while implementing data

Qualifications

• Strong Python, PySpark and SQL capability with distributed processing and automated testing.
• Hands‑on experience with Databricks, Apache Spark and Delta Lake for production data engineering.
• AWS data engineering experience with S3, Glue, Lake Formation, IAM, KMS, Lambda, Step Functions, EventBridge, CloudWatch, Redshift, MSK/Kinesis.
• Experience designing lakehouse or data‑lake architectures with layered data patterns and reusable datasets.
• Experience implementing incremental ingestion, change data capture and data quality in production pipelines.
• Familiarity with CI/CD, Terraform and environment promotion controls.

Responsibilities

• Lead design and delivery of batch and streaming data pipelines across AWS and Databricks.
• Design Bronze, Silver and Gold data layers with Delta Lake or equivalent patterns; develop data models and data products.
• Implement reliable ingestion from databases, files, APIs and event streams with various processing patterns.
• Establish data contracts, schema validation and data quality checks across pipelines.
• Build workflows using Databricks Workflows or Lakeflow; integrate tests and infrastructure as code; enable CI/CD.
• Implement metadata, lineage and governance with Unity Catalog, AWS Glue Data Catalog or Lake Formation.
• Define dashboards, alerts and runbooks for pipeline health and data quality; troubleshoot root causes.
• Optimise Spark/SQL workloads and cost efficiency; tune cluster configuration and data partitioning.
• Apply least-privilege security, encryption and audit logging across pipelines.
• Review designs and code; mentor engineers and promote reusable components.
• Collaborate with data owners, analysts, data scientists and governance teams to define data specifications.
• Document architecture decisions, data models and operating procedures; transfer knowledge to the team.

Skills

Python

PySpark

SQL

Databricks

Apache Spark

AWS

Data modeling

Delta Lake

Data pipelines

CI/CD

Tools

Databricks Unity Catalog

Airflow

Terraform

Kinesis

Glue

Unity Catalog

Job description

Activate Interactive Pte Ltd (“Activate”) is a leading technology consultancy headquartered in Singapore with a presence in Malaysia and Indonesia. Our clients are empowered with quality, cost-effective, and impactful end-to-end application development, like mobile and web applications, and cloud technology that remove technology roadblocks and increase their business efficiency.

We believe in positively impacting the lives of people around us and the environment we live in through the use of technology. Hence, we are committed to providing a conducive environment for all employees to realise their full potential, who in turn have the opportunity to continuously drive innovation.

We are searching for our next team members to join our growing team.

If you love the idea of being part of a growing company with exciting prospects in mobile and web technologies that create positive impact on people’s lives, then we would love to hear from you.

Co-Development Business Unit is hiring for Senior Data Engineer

You will work in Singapore Government Agencies

This is a fixed term contract role. The engagement is 1 year.

Internal Code: A26408

What will you do?

The Senior Data Engineer sits within the DSAD Platform and Architecture Team and is responsible for designing, building, productionising and operating trusted data pipelines and reusable data products on the SWDA data platform using AWS and Databricks. The role will provide technical leadership across data ingestion, transformation, modelling, quality, lineage, orchestration, observability and performance, applying CRISPr principles of comprehensiveness, robustness and scalability so that data remains dependable for analytics, reporting and ML/AI workloads.

• Data Pipeline Architecture and Delivery: Lead the design and implementation of maintainable batch and streaming pipelines that ingest, validate, transform and publish structured, semi-structured and unstructured data across AWS and Databricks.
• Lakehouse and Data Product Engineering: Design Bronze, Silver and Gold data layers using Delta Lake or equivalent patterns; develop reusable domain data models, curated datasets and data products with explicit ownership, definitions and service expectations.
• Source Integration and Incremental Processing: Implement reliable ingestion from databases, files, APIs and event streams using full-load, incremental, change-data-capture and replayable processing patterns appropriate to each source.
• Data Quality and Contracts: Establish schema enforcement, data contracts, automated validation, reconciliation and anomaly checks covering completeness, validity, consistency, uniqueness, timeliness and referential integrity.
• Orchestration and Deployment Automation: Build parameterised workflows using Databricks Workflows or Lakeflow and relevant AWS services; integrate automated testing, infrastructure as code and CI/CD controls across development, test and production environments.
• Metadata, Lineage and Governance: Implement technical metadata, business definitions, end-to-end lineage, classification, ownership and access controls using Unity Catalog, AWS Glue Data Catalog, Lake Formation or approved platform capabilities.
• Pipeline Monitoring and Reliability: Define dashboards, alerts, logging, operational metrics and runbooks for pipeline health, freshness, data-quality failures, latency, throughput and downstream impact; lead troubleshooting and root-cause analysis.
• Performance and Cost Optimisation: Optimise Spark and SQL workloads, file sizes, partitioning, clustering, caching, compaction, cluster configuration and workload scheduling to improve runtime, reliability and AWS/Databricks cost efficiency.
• Security and Data Protection: Apply least-privilege IAM, encryption, secrets management, environment separation, audit logging, sensitive-data controls and secure data-sharing patterns in line with applicable agency requirements.
• Technical Leadership and Quality: Set engineering standards, review designs and code, mentor engineers, manage technical debt and promote reusable components rather than project‑specific pipelines.
• Stakeholder Collaboration: Work with data owners, stewards, analysts, data scientists, architects, product teams and governance stakeholders to translate analytical and operational needs into implementable data specifications.
• Documentation and Knowledge Transfer: Maintain architecture decisions, source-to-target mappings, data models, contracts, operating procedures and support documentation, and transfer knowledge to the internal team throughout the engagement.

What are we looking for?

• Strong Python, PySpark and SQL capability, including distributed processing, complex transformations, query optimisation, debugging and automated testing.
• Hands‑on experience with Databricks, Apache Spark and Delta Lake for production‑scale batch or streaming data engineering.
• Hands‑on AWS data engineering experience with a relevant mix of S3, Glue, Lake Formation, IAM, KMS, Lambda, Step Functions, EventBridge, CloudWatch, Redshift and MSK/Kinesis.
• Experience designing lakehouse or data‑lake architectures, including layered data patterns, dimensional or domain data modelling and reusable curated datasets.
• Experience implementing incremental ingestion, change data capture, idempotency, late‑arriving data handling, backfills, replay and recovery.
• Experience implementing data quality, schema validation, reconciliation, metadata and lineage as automated parts of production pipelines.
• Experience with workflow orchestration, Git‑based development, CI/CD, infrastructure as code such as Terraform, and environment promotion controls.
• Ability to implement pipeline observability, operational dashboards, alerting, runbooks, incident diagnosis and service recovery.
• Working knowledge of cloud security, least‑privilege access, network boundaries, encryption, secret management, data classification and audit logging.
• Ability to review technical designs and code, establish engineering standards, and guide less‑experienced engineers.
• Experience with Databricks Unity Catalog, Lakeflow or Delta Live Tables, Auto Loader, Structured Streaming, Delta Sharing and Databricks Asset Bundles.
• Experience with Apache Airflow, dbt, Kafka, Amazon MSK/Kinesis, AWS DMS or equivalent ingestion and orchestration technologies.
• Experience designing data products, data contracts, semantic or context layers, master/reference data patterns or data mesh‑aligned operating models.
• Experience supporting feature engineering, ML training datasets, feature stores or MLOps pipelines on Databricks and AWS.
• Experience in Singapore public‑sector environments, including IM8‑aligned controls, data classification, VAPT, system assurance or governed cross‑agency data sharing
• Relevant certifications such as Databricks Certified Data Engineer Professional, AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect – Associate/Professional.Strong analytical and systems‑thinking capability, with the discipline to identify failure modes, edge cases and operational dependencies before production deployment.
• Clear written and verbal communication, including the ability to explain data architecture, quality, lineage, security, cost and delivery trade‑offs to technical and management audiences.
• Collaborative working style across data engineering, platform engineering, analytics, data science, architecture, cybersecurity and governance teams.
• Ability to translate ambiguous business needs into clear data definitions, contracts, acceptance criteria and incremental delivery plans.
• Strong ownership and production mindset, including careful documentation, support readiness and follow‑through on incidents and technical debt.
• Ability to mentor engineers constructively, raise engineering standards and build sustainable in‑house capability rather than creating vendor dependency.

Reference Framework

This role is informed by GovTech Singapore’s CRISPr framework for data‑pipeline design and monitoring. CRISPr describes a structured approach to designing and managing pipelines, with emphasis on comprehensiveness, robustness and scalability, to help agencies manage data complexity and improve data quality. The responsibilities above translate those principles into practical expectations for AWS and Databricks delivery.

Reference: https://practice.gto.tech.gov.sg/data/content/frameworks/crispr/introduction/introduction/

What do we offer in return?

Competitive Compensation

Market competitive salary and variable performance bonus aligned to your skills, impact, and contribution.

Benefits

Outpatient medical, specialist medical coverage and generouscustomisableflexi benefits, or flexi allowance; life and health insurance, thoughtfulperkslike special occasions “red packet” and CNY goodies, etc.

Employee Wellness

Support foryour physical, mental, and overall well‑being through year‑round initiatives.

Growth & Development

Learningprogrammes, certification support, and a dedicated staff development budget. (We are a “SHRI 2025 Gold winner” in “Learning & Development; Coaching & Mentoring”)

Career Progression

Structured career pathways that enable you to grow along a technical/domain expert track ora leadershiptrack.

Competency Framework

A structured and practical framework to support you to develop, perform, and succeed.

Flexible Work Arrangement

Staff may choose to work flexi-place,flexi-time, and flexi-load based on existing framework

Whyyou'lllove working with us?

If you are looking for opportunities to collaborate with leading industry experts andbesurrounded by highly motivated and talented peers, we welcome you to join us. We provide all employees with equal opportunities to grow and develop with us. Webelieveyour success is our success.

Activate Interactive Singapore is an equal opportunity employer. Employment decisions will be based on merit,qualificationsand abilities. Activate Interactive Pte Ltd does not discriminate in employment opportunities or practiceson the basis ofrace,colour, religion,gender, sexuality, national origin, age, disability, maritalstatusor any other characteristics protected by law.

Protecting your privacy and the security of your data are longstanding top priorities for Activate Interactive Pte Ltd.

Your personal data will be processed for the purposes of managing Activate Interactive PteLtd’srecruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring processes.

Please consult our Privacy Notice https://www.activate.sg/privacy-policy toknowmore about how we collect, use, and transfer the personal data of our candidates. Here you can find how you can request for access, correction and/or withdrawal of your Personal Data.