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SabPaisa
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Data Scientist

Data Scientist

SabPaisa

8 years

0 Lacs

New Delhi Delhi India

Posted:4 days ago| Platform:

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Skills Required

data modeler etl pipeline integrity collaborative interfacing engineering analytics compliance design logical support reporting processing sql orchestration airflow databricks governance security profiling query tuning spark talend transactions reconciliation audit aws gcp azure kafka architecture certifications python

Work Mode

On-site

Job Type

Full Time

Job Description

Location:

Experience:

Industry:

Job Summary

Data Modeler / Architect

You will play a key role in designing scalable data models, orchestrating reliable data workflows, and ensuring the integrity and performance of mission-critical financial datasets. This is a highly collaborative role interfacing with engineering, analytics, product, and compliance teams.

Key Responsibilities

Design, implement, and maintain
logical and physical data models
to support transactional, analytical, and reporting systems.
Develop and manage scalable
ETL/ELT pipelines
for processing large volumes of
financial transaction data
.
Tune and optimize
SQL queries, stored procedures
, and data transformations for maximum performance.
Build and manage
data orchestration workflows
using tools like
Airflow, Dagster, or Luigi
.
Architect data lakes and warehouses using platforms like
Databricks, Snowflake, BigQuery
, or
Redshift
.
Enforce and uphold
data governance, security, and compliance standards
(e.g., PCI-DSS, GDPR).
Collaborate closely with
data engineers, analysts, and business stakeholders
to understand data needs and deliver solutions.
Conduct
data profiling, validation
, and quality assurance to ensure clean and consistent data.
Maintain clear and comprehensive
documentation
for data models, pipelines, and architecture.

Required Skills & Qualifications

5–8 years of experience as a
Data Modeler, Data Architect
, or
Senior Data Engineer
in the
financial/payments
domain.
Advanced SQL expertise, including
query tuning, indexing
, and
performance optimization
.
Proficiency in developing ETL/ELT workflows using tools such as
Spark, dbt, Talend, or Informatica
.
Experience with data orchestration frameworks:
Airflow, Dagster, Luigi
, etc.
Strong hands-on experience with cloud-based data platforms like
Databricks, Snowflake
, or equivalents.
Deep understanding of
data warehousing principles
: star/snowflake schema, slowly changing dimensions, etc.
Familiarity with
financial data structures
, such as payment transactions, reconciliation, fraud patterns, and audit trails.
Working knowledge of
cloud services
(AWS, GCP, or Azure) and
data security best practices
.
Strong analytical thinking and problem-solving capabilities in high-scale environments.

Preferred Qualifications

Experience with
real-time data pipelines
(e.g., Kafka, Spark Streaming).
Exposure to
data mesh
or
data fabric
architecture paradigms.
Certifications in
Snowflake, Databricks
, or relevant cloud platforms.
Knowledge of
Python or Scala
for data engineering tasks.

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