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.

Work arrangement
Yes