Senior Engineer, Data Platform
Bangalore, India
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingBuild and operate Lakehouse, Spark, and distributed data-processing systems.
Improve the performance, reliability, cost, and operational visibility of platform workloads.
Develop capabilities for data quality, governance, lineage, metadata, discoverability, security, and access control.
From the employer’s posting
Responsibilities: Build and operate Lakehouse, Spark, and distributed data-processing systems. Improve the performance, reliability, cost, and operational visibility of platform workloads.
Build and operate Lakehouse, Spark, and distributed data-processing systems. Improve the performance, reliability, cost, and operational visibility of platform workloads. Develop capabilities for data quality, governance, lineage, metadata, discoverability, security, and access control.
Improve the performance, reliability, cost, and operational visibility of platform workloads. Develop capabilities for data quality, governance, lineage, metadata, discoverability, security, and access control. Build the data context required for trusted reporting, ML models, and AI agents.
What you’ll bring
All qualificationsCore experience
- 7+ years of software engineering experience.
- Strong experience in Python, Scala, Java, or another JVM language.
- Experience with Spark or another distributed data-processing framework.
- Experience building or operating production data platforms, backend systems, or distributed systems.
- Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP.
- Experience improving production reliability through monitoring, alerting, deployment automation, and incident response.
Preferred experience
- Experience with Kubernetes, Terraform, Airflow, Trino, ClickHouse, Starrocks, or Pinot is a plus.
Qualification wording
7+ years of software engineering experience.
Strong experience in Python, Scala, Java, or another JVM language.
Experience with Spark or another distributed data-processing framework.
Experience building or operating production data platforms, backend systems, or distributed systems.
Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP.
Experience improving production reliability through monitoring, alerting, deployment automation, and incident response.
Experience with Kubernetes, Terraform, Airflow, Trino, ClickHouse, Starrocks, or Pinot is a plus.
Tools in this posting
- Java
- AWS
- Hadoop
- Iceberg
- Kubernetes
- S3
- Spark
- Terraform
- Airflow
- Python
- Scala
- ClickHouse
- Trino
Source — Tool mentions in context
- 7+ years of software engineering experience. - Strong experience in Python, Scala, Java, or another JVM language. - Experience with Spark or another distributed data-processing framework.
- Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP. - Working knowledge of AWS services such as EC2, S3, Athena, and IAM. - Experience improving production reliability through monitoring, alerting, deployment automation, and incident response.
This is a broad platform role. Engineers on the team take ownership across Lakehouse architecture, distributed compute, data quality, governance, lineage, security, access controls, and the operational systems that keep the platform running. Individual focus areas will change with team priorities, and you will contribute across the platform as needed. The team also develops tooling for type-safe, testable data pipelines and operates Spark workloads on dynamically sized Hadoop clusters backed by EC2 Spot instances. We work closely with data engineers, data scientists, infrastructure teams, and product teams to make data dependable, easy to find, secure to use, and cost-effective to process. Responsibilities:
- Experience building or operating production data platforms, backend systems, or distributed systems. - Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP. - Working knowledge of AWS services such as EC2, S3, Athena, and IAM.
- Strong analytical, communication, and collaboration skills. - Experience with Kubernetes, Terraform, Airflow, Trino, ClickHouse, Starrocks, or Pinot is a plus. Company Summary:
- Strong experience in Python, Scala, Java, or another JVM language. - Experience with Spark or another distributed data-processing framework. - Experience building or operating production data platforms, backend systems, or distributed systems.
Job description
As a Senior Data Platform Engineer, you will build and operate the data infrastructure that supports Zeta’s products, analytics, machine learning, and AI systems.
This is a broad platform role. Engineers on the team take ownership across Lakehouse architecture, distributed compute, data quality, governance, lineage, security, access controls, and the operational systems that keep the platform running. Individual focus areas will change with team priorities, and you will contribute across the platform as needed.
The team also develops tooling for type-safe, testable data pipelines and operates Spark workloads on dynamically sized Hadoop clusters backed by EC2 Spot instances. We work closely with data engineers, data scientists, infrastructure teams, and product teams to make data dependable, easy to find, secure to use, and cost-effective to process.
Responsibilities:
- Build and operate Lakehouse, Spark, and distributed data-processing systems.
- Improve the performance, reliability, cost, and operational visibility of platform workloads.
- Develop capabilities for data quality, governance, lineage, metadata, discoverability, security, and access control.
- Build the data context required for trusted reporting, ML models, and AI agents.
- Evaluate compute and query engines for read-heavy workloads, assessing cost, performance, reliability, and operational fit.
- Assess real-time OLAP technologies and identify appropriate production use cases.
- Improve deployment, observability, incident response, developer tooling, and platform operations.
- Partner with data scientists and data engineers to improve their experience using the platform.
- Contribute fixes and improvements to relevant open-source projects, including Spark, Iceberg, and Airflow.
- Mentor engineers through code reviews, pairing, design discussions, and knowledge-sharing sessions.
Qualifications:
- 7+ years of software engineering experience.
- Strong experience in Python, Scala, Java, or another JVM language.
- Experience with Spark or another distributed data-processing framework.
- Experience building or operating production data platforms, backend systems, or distributed systems.
- Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP.
- Working knowledge of AWS services such as EC2, S3, Athena, and IAM.
- Experience improving production reliability through monitoring, alerting, deployment automation, and incident response.
- Strong analytical, communication, and collaboration skills.
- Experience with Kubernetes, Terraform, Airflow, Trino, ClickHouse, Starrocks, or Pinot is a plus.
Company Summary:
Zeta Global is a data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.
Zeta Global is a leading AI-powered marketing technology company that enables enterprise brands to acquire, grow, and retain customers through intelligent, data-driven engagement. At the center of its innovation is the Zeta Marketing Platform (ZMP), which unifies customer data, identity, and advanced analytics to transform billions of data signals into actionable marketing intelligence and measurable business outcomes.
Publicly traded on the New York Stock Exchange (NYSE: ZETA), Zeta is redefining modern marketing with Athena by Zeta™, a superintelligent, conversational agent embedded in ZMP that personalizes the marketer’s workspace, surfaces platform generated insights through natural dialogue and recommends next-best actions to help brands accelerate and optimize their marketing outcomes.
Learn more about Zeta:
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
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Source & posting history
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bangalore, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Oct 4, 2026
- Recorded sightings
- 6
- Last seen by us
- Oct 8, 2026
- Employer says posted
- Oct 2, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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