IND - Senior Staff Engineer, Reliability at The Hartford

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

19 Jul, 26

Salary

0.0

Posted On

20 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Reliability, Data Observability, Informatica, Python, Pyspark, Amazon EMR, Hadoop, Snowflake, Data Engineering, Data Quality, AIOps, Apache Airflow, DataOps, Cloud Engineering, Incident Management, Runbook Automation

Industry

Financial Services

Description

IND - Senior Staff Engineer, Reliability - GCC071 We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. Key Responsibilities Data Reliability & Quality: Establish and enforce Data Service Level Objectives (SLOs) focused on data freshness, completeness, and accuracy across critical data products. Data Observability: Implement advanced data observability tools to monitor the entire data journey—from ingestion to consumption—detecting data quality anomalies, schema drifts, and pipeline delays in real-time. Pipeline Resiliency & Automation: Collaborate with Data Engineering to embed reliability patterns into data pipelines built using Informatica, Python/Pyspark, and running on platforms like Amazon EMR/Hadoop, Informatica and cloud native services. Toil Elimination in Data Operations: Automate data validation, data reprocessing, data backfilling, and other manual operational tasks within the data lifecycle to reduce toil and improve operational efficiency. Incident and Problem Management (Data Focus): Lead the response and resolution for data-related incidents (e.g., corrupt data, delayed reporting), ensuring fast recovery and effective post-incident reviews (blameless post-mortems). Runbook Creation & Automation (Data Focus): Develop and automate sophisticated, data-aware runbooks for common data pipeline failures, data quality issues, and data recovery scenarios. Required Skills & Experience 10+ year’s overall experience in an Infrastructure, Data or related technology organization with increasing responsibilities as a hands-on technologist. 4-5+ year experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment. Expert level, hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP). Expert level experience in pipeline development and support using technologies like Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop). Experience in designing and implementing data quality checks, data validation frameworks, and data governance standards. Hands on experience in software or cloud engineering. Familiarity with cloud service providers and their core capabilities (compute, containers, databases, APIs etc.). In depth and hands on experience with data observability concepts and tools for monitoring data in motion and at rest (e.g., Monte Carlo, Bigeye, Astro Observe, Datafold, custom solutions). A strong understanding of the "data journey" and the impact of data issues on business outcomes. Expertise implementing AIOps to monitor, manage and self-heal data pipelines, using machine learning principles for anomaly detection. Experience with prompt engineering, implementing AWS or Google AI services, AI enabled automation for data quality, reliability and pipeline performance management. Expertise implementing and managing Apache Airflow workflows. Expertise defining and implementing of DataOps practices About Us | Our Culture | What It’s Like to Work Here Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day. About Us Our Culture What It’s Like to Work Here Perks & Benefits Legal Notice Accessibility Statement Producer Compensation EEO Privacy Policy California Privacy Policy Your California Privacy Choices International Privacy Policy Canadian Privacy Policy Unincorporated Areas of LA County, CA (Applicant Information) MA Applicant Notice Hartford India Prospective Personnel Privacy Notice

Responsibilities

The Senior Staff Engineer will establish data service level objectives and implement advanced observability tools to monitor data pipelines. They will also lead incident management efforts and automate operational tasks to improve data reliability and efficiency.