Arun S.

Product Manager

Amsterdam, Netherlands8 yrs 9 mos experience

Key Highlights

Expert in building cloud-native data platforms.
Proven track record in optimising large-scale data workflows.
Strong focus on enabling analytics and ML teams.

Stackforce AI infers this person is a Data Platform Engineer with expertise in Fintech and Telecommunications.

Contact

Skills

Core Skills

Platform ArchitectureData ArchitectsBig DataHadoop

Other Skills

AirflowAnsibleApache DruidApache KafkaApache NiFiApache SparkApache Spark StreamingAzure DevOpsCDHCDPClickHouseClouderaData LoadingDatabasesDevOps

About

Senior data platform engineer with experience building and operating large-scale distributed systems, cloud-native data platforms and lakehouse architectures. Worked with multi-petabyte environments, high-volume Spark workloads, and Kubernetes-based data processing. Skilled in data platform design, ingestion patterns, streaming and batch pipelines, cluster optimisation, CI/CD for data, and modernising legacy platforms. Strong focus on reliability, performance and enabling analytics and ML teams with stable, well-structured data foundations. Interested in senior roles in data platform engineering, data architecture, and scalable data infrastructure across the Netherlands.

Experience

8 yrs 9 mos

Total Experience

1 yr 5 mos

Average Tenure

Current Experience

Ing

Senior Data Platform Engineer

Jan 2024 – Present · 2 yrs 4 mos · Amsterdam Area · On-site

Shaped the architecture for ING’s real-time data ingestion and telemetry platform, improving data availability for analytics and reducing troubleshooting time across teams.
Designed the production data architecture for the Change Reliability Indicator (CRI), enabling consistent ML scoring and strengthening risk-based decision making.
Defined platform standards for streaming and batch pipelines, improving data quality, simplifying onboarding for new teams and making operations more predictable.
Led the transition from a legacy data lake to an Iceberg-based lakehouse, resulting in better governance, faster queries and a more maintainable data foundation.
Created deployment patterns for Spark on Kubernetes/OpenShift, improving workload stability and reducing operational overhead for engineering and platform teams.
Worked closely with platform, infra, security and data science groups to align architectural decisions with compliance, performance and long-term platform strategy.

HadoopPythonKubernetesAnsiblePandas (Software)Scikit-Learn+27

Booking.com

Booking.com (via Tavant) — Associate Technical Architect

Jul 2022 – Jan 2024 · 1 yr 6 mos · Amsterdam Area · On-site

Architect for a 5,000+ node, 600+ PB bare-metal data platform supporting large-scale analytics, ML workloads and business-critical data products.
Optimised 4,000–7,000 daily Spark and Hive jobs, improving runtime stability, reducing failures and enabling predictable ML training and feature pipelines.
Introduced cloud-native design patterns to modernise legacy workloads and prepare the platform for containerised and hybrid deployments.
Built and maintained a custom Hadoop distribution using Apache Bigtop, reducing operational complexity and enabling faster, controlled upgrades across thousands of nodes.
Developed automated deployment and configuration frameworks, improving rollout speed, consistency and overall platform reliability.
Enhanced observability for Spark, YARN, Hive and HDFS, enabling quicker insight into performance bottlenecks and reducing impact on downstream analytics and ML inference.
Worked with data engineering, infra, ML platform and SRE teams to align architectural decisions with performance goals, cost efficiency and long-term platform strategy.

HadoopBig DataDatabasesPuppet (Software)Open SourceDevOps+8

Rabobank

Platform Engineer

Sep 2021 – Jul 2022 · 10 mos · Utrecht, Netherlands

Supported and improved Rabobank’s data platform environments, including Cloudera (CDH/CDP) and Dataiku, ensuring stable and secure operations for analytics and ML teams.
Led the platform migration from CDH to CDP, improving governance, security integration and long-term maintainability of the bank’s data ecosystem.
Automated deployment, monitoring and patching workflows using Azure Pipelines, reducing manual operations and increasing platform reliability.
Implemented Spark-on-Kubernetes processing patterns, enabling more scalable and cloud-aligned data workloads.
Enhanced platform performance and stability through tuning, capacity planning and proactive issue identification across Hadoop and Kubernetes environments.
Partnered with data science, infra and security teams to align platform capabilities with business needs and compliance requirements.

Big DataCDHZabbixGrafanaCDPHadoop+6

Nagarro

Lead Engineer

Apr 2020 – Aug 2021 · 1 yr 4 mos · Gurugram, Haryana, India

Supported the architecture and scaling of distributed data workflows across Hadoop, YARN and Cassandra, improving performance and stability for high-volume analytics.
Delivered monitoring and observability solutions using Telegraf, InfluxDB and Grafana, enabling teams to troubleshoot issues faster and operate the platform more confidently.
Optimised data processing pipelines and storage strategies, contributing to more predictable and efficient platform behaviour under increasing load.
Worked with cross-functional engineering teams to align data platform improvements with business requirements and operational needs.

Big DataGlusterFSHadoopApache SparkPython (Programming Language)

Airtel x labs

Senior Software Engineer

Mar 2018 – Apr 2020 · 2 yrs 1 mo · Gurgaon, Haryana, India

Contributed to the architecture and operation of a multi-petabyte customer analytics platform integrating 600+ data sources across network, product and customer domains.
Improved reliability and performance across Hadoop clusters, enabling faster analytics and supporting business teams with more timely insights.
Designed and maintained data pipelines and ingestion flows that supported critical applications across Airtel’s digital ecosystem.
Implemented automation for CI/CD and platform operations, reducing deployment time and increasing consistency across environments.
Collaborated with analytics, product and platform teams to ensure data availability, governance alignment and platform stability for downstream use cases.

Platform ArchitectureData ArchitectsPython (Programming Language)AnsibleZabbixApache Spark+11