ORIGINAL JOB DESCRIPTION
About the Job
Senior Data Platform Engineer
Company: Intellias
Education: Bachelor’s Degree
Experience Level: Senior
About Intellias
Let’s breathe life into great tech ideas!
With 3,000 people globally, Intellias is a technology company where benchmark technological solutions are born. Join our team and contribute to digitalizing the world by building innovative, scalable, and reliable technology solutions.
At Intellias, people come before processes. We foster a technology-driven environment where professionals can grow, take ownership, and make a meaningful impact.
Project Overview
Our client is building a standardized, governed data-sharing platform that enables product services, analytics, and AI/ML systems to share and consume data securely and reliably.
The Data Platform team is responsible for establishing the contracts, controls, publishing workflows, catalog metadata, lifecycle management, lineage, permissions, and runtime components required to make reusable data safe and practical at scale.
This is an opportunity to shape a platform from an early stage while solving real production challenges. The client already operates production systems, a Kafka backbone, PostgreSQL databases, analytical consumers, and AI/ML use cases. The goal is to establish a consistent, developer-friendly approach to data publishing and consumption.
The initial milestone focuses on platform-managed publishing tables in service-owned PostgreSQL databases, change data capture (CDC) through Debezium into Kafka, and registration in DataHub with ownership, lifecycle, lineage, and impact-analysis metadata.
Over time, the platform will evolve toward self-service data products, governed materializations, durable shared state, and reusable data capabilities across operational and analytical systems.
As a Senior Data Platform Engineer, you will help design and build the foundational platform services and workflows that engineering teams will use to publish, govern, and consume shared data.
Responsibilities
Design, develop, and operate platform services, tools, and workflows for contract-driven data publishing and consumption.
Build the initial production workflow connecting platform-managed PostgreSQL publishing tables, Debezium CDC, Kafka topics, and DataHub catalog registration.
Develop GitOps-style workflows for managing data contracts, schemas, ownership, lifecycle rules, compatibility policies, metadata, and runtime configurations as code.
Build developer tooling, validation mechanisms, and automation that provide fast feedback before data products are published or modified.
Define and implement standards for data products, publishing contracts, schema evolution, field stability, deletion semantics, access policies, lineage, and cost attribution.
Operate and improve CDC infrastructure, including Kubernetes workloads, source isolation, offsets, schema history, heartbeats, signal channels, and replication-lag monitoring.
Implement reliable replay, resnapshotting, recovery, and failure-handling mechanisms for data replication workflows.
Integrate platform metadata with DataHub to enable data discovery, ownership transparency, lineage tracking, and impact analysis.
Apply distributed systems principles to ensure reliability, idempotency, compatibility, eventual consistency, and clear ownership boundaries.
Collaborate with product engineering, infrastructure, data engineering, analytics, and AI/ML teams to establish standardized, secure, and scalable data-sharing practices.
Translate evolving architectural direction into incremental, production-ready solutions while making technical trade-offs explicit.
Requirements
Strong experience building, deploying, and operating production software systems, preferably in platform engineering, infrastructure, backend engineering, or data-intensive environments.
Deep understanding of distributed systems concepts, including reliability, idempotency, replay, eventual consistency, compatibility, ownership boundaries, and operational failure modes.
Practical experience with PostgreSQL or other relational databases, including schema design, migrations, transactions, replication, and performance optimization.
Experience with Kafka, event streaming, change data capture (CDC), Debezium, or similar data-movement technologies.
Strong software engineering skills and experience building tools or platforms used by other engineers, such as CLIs, internal developer platforms, control planes, automation, CI validation, or self-service workflows.
Familiarity with Kubernetes and cloud or infrastructure platforms, including deployment, runtime isolation, observability, and operational ownership.
Ability to translate ambiguous architectural requirements into practical implementation plans and deliver production-ready solutions incrementally.
Strong problem-solving skills, sound technical judgment, and the ability to make informed trade-offs in evolving environments.
Excellent written and spoken English communication skills, with the ability to align multiple engineering teams around technical standards, contracts, and ownership boundaries.
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field.
Nice to Have
Experience with DataHub or other data catalog, lineage, metadata management, or data governance platforms.
Familiarity with open table formats such as Apache Iceberg and analytical storage technologies, including object-store-backed data lakes, Amazon S3, BigQuery, or ClickHouse.
Experience with GitHub Actions, policy-as-code, infrastructure-as-code, controllers, operators, or reconciliation-based systems.
Knowledge of data contracts, schema registries, Protobuf, Avro, JSON Schema, schema compatibility validation, field-level metadata, and contract testing.
Experience supporting analytics, AI/ML workloads, feature-store-style access patterns, or cross-domain product-service integrations.
Proficiency in one or more programming languages, such as JVM languages, Python, TypeScript, Go, or Ruby.
Why Join Intellias?
At Intellias, technology takes center stage, but people always come first. We create an environment where talented professionals can take ownership, solve meaningful engineering challenges, and continuously develop their expertise.
By joining this project, you will have the opportunity to:
Shape a platform from the ground up: Influence architectural decisions and establish engineering standards that will support multiple teams.
Solve real production challenges: Work with established systems and technologies while building a more reliable and scalable data foundation.
Make a lasting technical impact: Develop reusable platform capabilities that improve how product, analytics, and AI/ML teams share data.
Grow professionally: Expand your expertise in distributed systems, platform engineering, event streaming, and data governance.
Collaborate with experienced engineers: Work across technical domains to deliver practical solutions with measurable value.
Our customized benefits and people-first culture support your well-being, professional growth, and long-term career development.
Join Intellias and help build the next generation of governed data-sharing platforms.
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