Senior Engineer, Data Platform

Zeta Global

Bangalore, India

Who this role is best for

Data platform professionals with 7+ years of experience in building distributed systems and working with Spark will find this role challenging and impactful, especially in a collaborative, geographically focused setting.

Best fit for

Candidates with deep expertise in Spark and distributed data-processing systems, and a track record in data governance and security
— “Build and operate Lakehouse, Spark, and distributed data-processing systems.”
Individuals who have contributed to open-source projects like Spark or Airflow and are comfortable with evolving priorities
— “Contribute fixes and improvements to relevant open-source projects, including Spark, Iceberg, and Airflow.”
Professionals who have experience optimizing data platforms for cost, performance, and reliability in production environments
— “Improve the performance, reliability, cost, and operational visibility of platform workloads.”

Things to consider

The role demands hands-on experience with AWS services such as EC2, S3, and IAM in a production setting
— “Working knowledge of AWS services such as EC2, S3, Athena, and IAM.”
Candidates must be prepared to work across multiple domains, including data quality, governance, and real-time OLAP technologies
— “Familiarity with at least 1 of these areas: Lakehouse architecture, Apache Iceberg, data quality, governance, lineage, metadata, query engines, or real-time OLAP.”

How to stand out

Highlight experience with building and operating large-scale data platforms, not just individual components
— “Build and operate the data infrastructure that supports Zeta’s products, analytics, machine learning, and AI systems.”
Emphasize your ability to evaluate and implement query engines and real-time OLAP technologies for production use
— “Assess real-time OLAP technologies and identify appropriate production use cases.”
Demonstrate your ability to improve deployment and incident response processes for data systems
— “Improve deployment, observability, incident response, developer tooling, and platform operations.”
Demonstrate experience with dynamic compute environments and cost-optimization strategies for data workloads
— “operates Spark workloads on dynamically sized Hadoop clusters backed by EC2 Spot instances.”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

operating Lakehouse, Spark, and distributed data-processing systems
improving platform workloads
developing data quality and governance capabilities

Typical background

7+ years of software engineering experiencestrong experience in Python, Scala, Java, or another JVM language

Skills & requirements

Required

Lakehouse ArchitectureDistributed ComputeData QualityGovernanceLineageSecurityAccess ControlsSparkHadoopEC2 Spot InstancesAWS ServicesKubernetesTerraformAirflowTrinoClickhouseStarrocksPinot

Preferred

PythonScalaJavaIcebergData QualityGovernanceLineageMetadataQuery EnginesReal-time OLAP

Stack & domain

Lakehouse ArchitectureDistributed ComputeData QualityGovernanceLineageSecurityAccess ControlsSparkHadoopEC2 Spot InstancesData PipelinesType-safeTestableAIMLData-driven SolutionsData EngineeringData ScienceInfrastructureProduct TeamsData ContextTrusted ReportingML ModelsAI AgentsCompute And Query EnginesReal-time OLAPDeploymentObservabilityIncident ResponseDeveloper ToolingPlatform OperationsKubernetesTerraformAirflowTrinoClickhouseStarrocksPinotProblem-solvingTeamworkCommunicationAdaptabilityCreativityAttention To DetailTime ManagementLeadershipData PlatformsMarketing TechnologyCustomer DataIdentityAdvanced Analytics

About the role

Original posting from Zeta Global via Greenhouse

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:
https://zetaglobal.com/press-news/

Source: Zeta Global careers (Greenhouse)