Data Engineer – AWS Observability

TekIT Software Solutions Pvt. Ltd. (India & USA)

5 years

0 Lacs

Pune Maharashtra India

Posted:3 days ago| Platform:

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Skills Required

data aws development monitoring reporting leadership engineering vision design architecture code support tuning software programming pyspark devops git jenkins management agile jira

Work Mode

On-site

Job Type

Full Time

Job Description

Technical Lead – Data Observability

The ideal candidate will have strong technical acumen in AWS data services, proven leadership experience in engineering teams, and a passion for building scalable, high-performance cloud-based data pipelines.

You will work closely with the Programme Technical Lead / Architect to define the platform vision, technical priorities, and key success metrics.

Key Responsibilities:

Lead the
design, development, and deployment
of features for the data observability platform.
Mentor and guide junior engineers, fostering a culture of
technical excellence and collaboration
.
Collaborate with architects to align on
roadmap, architecture, and KPIs
for platform evolution.
Ensure
code quality, performance, and scalability
across data engineering solutions.
Conduct and participate in
code reviews, architecture design discussions, and sprint planning
.
Support
operational readiness
including performance tuning, alerting, and incident response.

Must-Have Skills & Experience (Non-Negotiable):

5+ years
of hands-on experience in Data Engineering or Software Engineering.
3+ years
in a technical lead/squad lead capacity.
Expertise in
AWS Data Services
:
AWS Glue
AWS EMR
Amazon Kinesis
AWS Lambda
Amazon Athena
Amazon S3
Strong programming skills in
PySpark, Python
, and
SQL
.
Proven experience in building and maintaining
scalable, production-grade data pipelines
on cloud platforms.

💡 Preferred / Nice-to-Have Skills:

Familiarity with
Data Observability tools
(e.g., Monte Carlo, Databand, Bigeye) is a plus.
Understanding of
DevOps/CI-CD practices
using Git, Jenkins, etc.
Knowledge of
data quality frameworks
, metadata management, and data lineage concepts.
Exposure to
agile methodologies
and tools like Jira, Confluence.

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