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Data Engineer

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Hybrid

Data Engineer

Stovl Consulting

Data Engineer

Skills

SQL QueriesData EngineeringTableauPythonRData AnalysisAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Hybrid

Published on:

24 August 2026

What they need


S T O V L C O N S U L T I N G P R I V A T E L I M I T E D
Data Engineer
Bangalore, India Full-Time 4-5 Years Experience
A B O UT ST OV L
Stovl has evolved from data center services into end-to-end system lifecycle delivery, combining
Product Engineering, Cloud Automation, Data Engineering, Artificial Intelligence, and
Cybersecurity to build cohesive, operable platforms. We operate as a global delivery firm
supporting customers across the US, India, and Singapore serving fintech, insurance, SaaS,
industrial IoT, and regulated enterprises.

P OS IT IO N OV E RV IE W
We are looking for a Data Engineer in Bangalore to help deliver reliable, business-facing data
solutions that improve decision-making across the organization. This role is ideal for someone
with strong SQL skills, hands-on experience building and supporting ETL/ELT workflows, and a
practical understanding of how data quality, governance, and operational ownership contribute
to trusted reporting.
The right candidate will work closely with analytics teams, business stakeholders, and data
platform partners to build scalable datasets, support Tableau-based reporting, and improve the
overall quality and usability of data for decision-making

K E Y RE SP ON SIB I L IT IE S
Build, maintain, and enhance SQL-based data pipelines and transformation workflows that
support analytics and reporting needs.
Work with ETL/ELT tools to ingest, transform, validate, and publish data for business
consumption, with preference for experience in SnapLogic.
Take ownership of data quality, pipeline reliability, monitoring, and issue resolution across
assigned workflows.
Design and maintain dimensional and analytical data models that support consistent KPI
reporting and self-service analytics.
Partner with analysts and business stakeholders to translate requirements into scalable
datasets, dashboards, and reporting logic.
Develop and support Tableau data sources and dashboards, with a focus on usability,
performance, and trust in the underlying data.
Perform data validation, reconciliation, and root-cause analysis to identify and resolve
inconsistencies in reporting outputs.
Document business logic, data definitions, source-to-target mappings, dependencies, and
operational runbooks.
Contribute to continuous improvement in data engineering standards, governance
practices, and delivery processes.

R E Q UI RE D S KI LL S & Q U A LI F ICA T I ON S
Experience working with ETL/ELT tools and modern data workflows; SnapLogic experience
is strongly preferred.
Solid understanding of data quality practices, governance principles, and operational
ownership of production data pipelines.
Experience designing dimensional and analytical data models for reporting and business
analytics.
Tableau development experience, including building or supporting dashboards, data
sources, and business-facing reporting solutions.

Python scripting experience for automation, validation, or lightweight data processing.
Ability to work with business users to understand requirements and translate them into
reliable technical solutions.

Strong analytical, troubleshooting, and communication skills.
Bachelors degree in Computer Science, Engineering, Information Systems, Analytics, or a
related field, or equivalent practical experience.

Experience supporting finance, sales, or marketing analytics use cases.
Experience working in a product company environment.
Familiarity with data governance frameworks, metric definitions, and reporting best
practices.

Exposure to cloud data platforms and modern analytics ecosystems.
S O FT S K IL LS
Strong problem-solving and analytical mindset
Ability to work independently and thrive in cross-functional team settings
Excellent communication and stakeholder collaboration skills
High ownership mindset with a bias for accountability and delivery

Wh a t S ucc ess Lo o ks L ike
Business-facing data outputs are timely, accurate, and trusted.
Pipelines and reporting datasets are reliable, well-documented, and easy to support.
Data quality issues are identified early and resolved with clear ownership.
Tableau dashboards are backed by stable, scalable, and consistent data sources.
Data models and transformation logic are reusable, maintainable, and aligned to business
definitions.
E D U C AT I ON
Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent
practical experience)
Stovl Consulting Private Limited www.stovl.com

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