Senior Software Engineer - Data Platform(Data Ingestion & Processing) at Harness

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

01 Jan, 26

Salary

0.0

Posted On

03 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Ingestion, Data Processing, Data Streaming, Distributed Systems, ETL Pipelines, SQLMesh, DBT, Spark Structured Streaming, Query Engines, OLAP Stores, Data Streaming Technologies, Java, Python, Open Table Architecture, OLTP Datastores, Production Data Systems

Industry

Software Development

Description

Harness is a high-growth company that is disrupting the software delivery market. Our mission is to enable the 30 million software developers in the world to deliver code to their users reliably, efficiently, securely and quickly, increasing customers’ pace of innovation while improving the developer experience. We offer solutions for every step of the software delivery lifecycle to build, test, secure, deploy and manage reliability, feature flags and cloud costs. The Harness Software Delivery Platform includes modules for CI, CD, Cloud Cost Management, Feature Flags, Service Reliability Management, Security Testing Orchestration, Chaos Engineering, Software Engineering Insights and continues to expand at an incredibly fast pace. Harness is led by technologist and entrepreneur Jyoti Bansal, who founded AppDynamics and sold it to Cisco for $3.7B. We’re backed with $425M in venture financing from top-tier VC and strategic firms, including J.P. Morgan, Capital One Ventures, Citi Ventures, ServiceNow, Splunk Ventures, Norwest Venture Partners, Adage Capital Partners, Balyasny Asset Management, Gaingels, Harmonic Growth Partners, Menlo Ventures, IVP, Unusual Ventures, GV (formerly Google Ventures), Alkeon Capital, Battery Ventures, Sorenson Capital, Thomvest Ventures and Silicon Valley Bank. Position Summary We are building a unified data platform to serve 20+ product modules, enabling ingestion, processing, and retrieval of data to power analytics & systems at scale. This role is part of the Data Ingestion charter under the Unified Data Platform umbrella, focused on designing and developing an extremely high-scale ingestion platform with focus on data streaming, open table based data storage, and highly scalable transformation layer. This platform is the foundation to multiple experiences within Harness including dashboard, analytics, and product utilization. About the Role You will participate in the design, architecture & development of this platform alongside principal engineers & architects, solving deep problems in data streaming, transformation, and extremely large scale data storage. You will work with multiple product engineering teams in an extremely collaborative fashion providing guidance to onboard onto the data platform. Author high level & low level design documents. Design and implement automation of infrastructure setup using helm, terraform and similar technologies. Work alongside Site Reliability Engineers and cross functional teams to diagnose/troubleshoot any production performance related issues About You Bachelor’s or Master’s degree in computer science 5+ years of hands-on software(backend) development experience - most of which should be in the data platform space involving distributed systems Hands on experience building ETL pipelines with technologies like SQLMesh, DBT, or Spark Structured Streaming Hands-on experience with query engines like Trino Deep exposure to OLAP stores like Pinot, Druid, Clickhouse, Starrocks, Snowflake, or Databricks Working experience with open table architecture such as Iceberg, Delta Lake or Hudi. Experience with data streaming technologies like Flink, Spark Streaming, Kafka Streams etc Familiarity with OLTP datastores such as MongoDB, PostgreSQL Experience scaling and operating production data systems at 10K+ QPS Deep working experience with Java and Python Harness in the news: Harness AI Tackles Software Development’s Real Bottleneck After 'Vibe Coding' Comes 'Vibe Testing' (Almost) Startup Within a Startup: Empowering Intrapreneurs for Scalable Innovation - Jyoti Bansal (Harness) Jyoti Bansal, Harness | theCUBEd Awards Eight years after selling AppDynamics to Cisco, Jyoti Bansal is pursuing an unusual merger Harness snags Split.io, as it goes all in on feature flags and experiments Exclusive: Jyoti Bansal-led Harness has raised $150 million in debt financing All qualified applicants will receive consideration for employment without regard to race, color, religion, sex or national origin. Note on Fraudulent Recruiting/Offers We have become aware that there may be fraudulent recruiting attempts being made by people posing as representatives of Harness. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers. Please note, we do not ask for sensitive or financial information via chat, text, or social media, and any email communications will come from the domain @harness.io. Additionally, Harness will never ask for any payment, fee to be paid, or purchases to be made by a job applicant. All applicants are encouraged to apply directly to our open jobs via our website. Interviews are generally conducted via Zoom video conference unless the candidate requests other accommodations. If you believe that you have been the target of an interview/offer scam by someone posing as a representative of Harness, please do not provide any personal or financial information and contact us immediately at security@harness.io. You can also find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commission’s website (https://consumer.ftc.gov/articles/job-scams), or you can contact your local law enforcement agency.

Responsibilities

You will participate in the design, architecture & development of a high-scale ingestion platform focused on data streaming and transformation. Collaborate with multiple product engineering teams to onboard onto the data platform and troubleshoot production performance issues.