Senior Engineer, Data Platform
At a glance
Senior Data Engineering role at zetaglobal. Bangalore.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and operate Lakehouse, Spark, and distributed processing infrastructure for the data platform
- Improve platform workloads by raising performance and reliability while controlling cost and visibility
- Create tools for data quality, governance, lineage, metadata discovery, security, and access
- Compare query engines for read-heavy tasks and assess production uses for real-time OLAP
- Improve operations and developer tools, support platform users, contribute open-source fixes, and mentor engineers
What you bring
- At least seven years of software engineering experience
- Strong ability in Python, Scala, Java, or another JVM language, with Spark or comparable distributed-processing experience
- Experience running production data platforms, backend systems, or distributed systems
- Hands-on familiarity with at least one listed data platform area, such as Lakehouse architecture, Iceberg, or data quality
- Knowledge of AWS offerings including EC2, S3, Athena, or IAM, plus experience improving production reliability
Who this fits
This senior role suits an engineer who can work across data infrastructure and platform operations as team priorities shift. You’ll collaborate with data scientists and engineers, and mentor peers through reviews, pairing, design discussions, and knowledge sharing.
From the employer
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:
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