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Home
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EliteSquad.AI
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Data Engineer

Data Engineer

EliteSquad.AI

3 years

0 Lacs

Ahmedabad Gujarat India

Posted:3 days ago| Platform:

Apply

Skills Required

data aws reconciliation integrity design etl redshift automate support finance accounting compliance analytics audit pipeline processing governance engineering scripting git power tableau audits kafka code terraform

Work Mode

On-site

Job Type

Full Time

Job Description

Job Title:

Location:

Experience:

Job Type:

About the Role:

Data Engineer

Key Responsibilities:

Design, develop, and maintain robust
ETL/ELT pipelines
using
AWS services
(e.g., AWS Glue, Lambda, Redshift, S3, Athena).
Reconcile large datasets from multiple financial systems, ensuring
data accuracy
,
completeness
, and
auditability
.
Automate data validation and reconciliation processes to support finance, accounting, and compliance teams.
Collaborate with cross-functional teams (finance, data analytics, business intelligence) to gather requirements and implement data solutions.
Create and maintain
data dictionaries
,
lineage documentation
, and
audit trails
for financial datasets.
Monitor pipeline performance and troubleshoot data quality or processing issues.
Implement data governance best practices and support regulatory and internal compliance needs.

Required Skills & Qualifications:

Minimum
3 years of experience
in data engineering or similar roles.
Proven experience working with
financial data
and
data reconciliation
(e.g., transactional data, ledger entries, settlements, P&L, balance sheets).
Strong experience with
AWS services
: S3, Glue, Lambda, Redshift, Athena, CloudWatch, Step Functions.
Strong in
SQL
and scripting languages such as
Python
or
Scala
.
Experience building and automating
data validation and reconciliation tools
or processes.
Familiarity with
data warehousing concepts
and
data lake architecture
.
Experience working with version control systems like Git and CI/CD pipelines.
Bachelor’s degree in Computer Science, Information Systems, Finance, or related field.

Nice to Have:

Understanding of accounting principles and finance domain KPIs.
Experience with
data visualization
and
BI tools
(e.g., Power BI, Tableau, AWS QuickSight).
Knowledge of
data quality frameworks
, audits, and controls.
Exposure to real-time data streaming platforms (e.g., Kafka, Kinesis).
Experience with infrastructure-as-code tools (Terraform, CloudFormation).

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