Sr Systems Engineer ( Data and Integrations)

Role: Sr Systems Engineer ( Data and Integrations)

Location: India/Remote

Shift Hours: Overlapping in US Hours

Long-term contract opportunity

Job Description:

About the Role

• Customer is building data pipelines to power the modern data stack for thousands of
• companies. We’re looking for a Senior Staff Systems Engineer, Data and Integrations to join
• our Systems Engineering team and set the technical direction for the data that runs customers
• ness. In this role, you will own the data architecture behind our marketing, sales, billing, and
• product operations: the canonical data models, the contracts between systems, and the
• pipelines and transformations that move data reliably between them. You will lead our largest
• and most consequential data initiatives, such as system migrations, org consolidations, and re-
• platforming of core integrations, from design through validation and cutover.
• This position sits at the crossroads of data engineering, data modeling, and business process.
• You will partner closely with our Systems, Analytics, and Engineering teams, as well as
• Marketing, Revenue Operations, Accounting, Product Operations, and other business partner
• teams, and you will mentor the engineers who build within the standards you set.

Technologies You’ll Use

• Our core systems are Salesforce, Netsuite, Coupa, Workday, and Zendesk, with BigQuery as
• our data warehouse. Our current integration stack includes Celigo and customer itself. You
• should be an expert in SQL and strong in a general purpose programming language such as
• Python or TypeScript, and comfortable evaluating and adopting new tools when necessary.
• A data engineering background is required, with expertise in data modeling, ETL/ELT
• development, data quality testing, and data validation at scale. Experience with dbt or a similar
• transformation framework, and with API-based and event-driven integration patterns, is
• preferred. Help us bring established data engineering practices to internal business systems,
• and define what those practices should be here.

What You’ll Do

Data Architecture and Standards

● Own the canonical data models for Customer marketing, sales, billing, and product

operations integrations, and define how business concepts map to data across our core

systems.

● Define team-wide standards for data modeling, data quality, testing, governance, and

documentation, and drive their adoption across Systems Engineering and partner teams.

● Contribute to the design of integration architecture, establishing guidance for when to

use batch, real-time, and event-driven data movement.

Delivery of Complex Initiatives

● Lead the design and execution of our most complex data initiatives, including bulk

migrations, system consolidations, and re-implementation of core integrations, from

target-state design through validation, cutover, and stabilization.

● Build, review, and ship the SQL and Python transformations and pipelines behind these

initiatives, setting the bar for code quality on the team.

● Design the validation and reconciliation approach for migrations and pipeline changes,

and sign off with stakeholders that record counts, values, and business rules reconcile.

Reliability and Observability

● Design the monitoring, alerting, and data quality framework that gives end-to-end

visibility into data freshness and accuracy across systems, and define the KPIs used to

measure integration and data health.

● Lead root cause analysis on the most complex cross-system data issues, and drive the

systemic fixes that prevent recurrence.

Business Partnership Technical Leadership

● Translate ambiguous requirements from cross-functional business partners into data

models and technical designs, and drive alignment across teams with competing

priorities.

● Serve as the technical lead and subject matter expert for business data within the

Systems Engineering team.

● Mentor other engineers and review their designs and code, raising the team's proficiency

in data modeling, testing, and pipeline design.

● Write and maintain design documents and data flow documentation for current and

target state, so decisions are legible to the team and to partners.

Skills We’re Looking For

● 10+ years of experience in Data Engineering, Analytics Engineering, or a similar role,

with a deep focus on modeling and transforming business data and a track record of

technical leadership on complex, multi-team initiatives.

● Expert SQL proficiency, including complex transformations, performance tuning, and

large-scale data reconciliation.

● Strong proficiency in a general purpose programming language such as Python or

TypeScript, with experience building production-grade, tested data pipelines.

● Hands-on experience with business systems data models such as those for Salesforce,

NetSuite, Coupa, Workday, or Zendesk, including a data migration, org merge, or major

re-implementation.

● Demonstrated experience designing and delivering large-scale ETL/ELT solutions and

the data quality, validation, and governance frameworks around them.

● Ability to evaluate trade-offs between short-term delivery and long-term data architecture

health, and to communicate those decisions clearly.

● Ability to lead through influence, driving alignment across technical and non-technical

stakeholders without direct authority.

Bonus Skills

● Experience with dbt or a similar transformation framework.

● Hands-on experience with iPaaS platforms such as Celigo, Workato, or Boomi, and with

reverse ETL tools, including experience choosing between them.

● Experience with cloud platforms such as AWS or GCP, infrastructure as code, and

CI/CD for data pipelines.

● Familiarity with AI/ML capabilities to augment data quality, matching, and automation.