Big Data Platform Engineer at COGNIZANT TECHNOLOGY SOLUTIONS ASIA PACIFIC PTE. LTD.
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Big Data Platform Engineer
COGNIZANT TECHNOLOGY SOLUTIONS ASIA PACIFIC PTE. LTD.
🇸🇬 Singapore4d ago
S$1,14,000 — S$1,50,000/year
≈ ₹71L — ₹94L per year
Expert SystemsScalaKubernetesBig Data FrameworkProgramming LanguagesHadoopVMApache KafkaDatastreamDocker ContainerPython ProgrammingData security platformsData
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You are operating Global Data Platform components (VM Servers, Kubernetes, Kafka) and applications (Apache Stack, Collibra, Databricks and similar).
Implement automation of infrastructure, security components, and Continuous Integration & Continuous Delivery (CI/CD) for optimal execution of data pipelines (ELT/ETL).
Develop solutions to build resiliency in data pipelines that perform health checks, monitoring, and alerting mechanisms; quality, timeliness, recency, and accuracy of the data delivery are improved.
Apply DevSecOps and Agile approaches to deliver a holistic and integrated solution in iterative increments.
Liaison and collaborate with enterprise security, digital engineering, and cloud operations architecture solution frameworks to drive consensus on design.
Review system issues, incidents, and alerts to identify root causes and continuously implement features to improve platform performance.
Be current on the latest industry developments and technology trends to effectively lead and design new features and capabilities.
Experience
You have 5+ years of experience in building or designing large‑scale, fault‑tolerant, distributed systems.
Migration experience of storage technologies (e.g. HDFS to S3 Object Storage).
Integration of streaming and file‑based data ingestion/consumption (Kafka, Control‑M, AWS).
Experience in DevOps, data pipeline development, and automation using Jenkins, Ansible, Chef, XL Release, and XL Deploy.
Experience predominantly with on‑prem Big Data architecture; cloud migration experience is welcome.
Hands‑on experience integrating Data Science Workbench platforms (e.g. Datiku).
Experience with Agile project management methods (e.g. Scrum, SAFe).
Supporting analytical value streams from enterprise reporting (e.g. Tableau) to data science (incl. ML Ops).
Skills
Hands‑on working knowledge of large data solutions (e.g. data lakes, delta lakes, data meshes, data lakehouses, data platforms, data streaming solutions).
In‑depth knowledge and experience in one or more large‑scale distributed technologies, including but not limited to:
Hadoop ecosystem
Kafka
Kubernetes
Spark
Expert in Python and Java or another programming language (Scala/R, Linux/Unix scripting).
VM setup and scaling (K8s scaling, managing Docker with Harbor, pushing images through CI/CD).
Experience using data formats such as Apache Parquet, ORC, Avro.
Exposure to machine learning algorithms is a plus.
Good knowledge of German is beneficial; excellent command of English is essential.
Knowledge of the financial sector and its products.