Data Engineer

Exponentia Team

5 - 10 years

5 - 8 Lacs

mumbai

Posted:10 hours ago| Platform:

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Skills Required

data modeling database design machine learning data quality microsoft aws monitoring sql data architecture python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Requirements Gathering & Analysis

Design, develop, and maintain data pipelines and ETL/ELT processes using AWS services such as Glue, Lambda, S3, Redshift, and Athena .
Build and optimize
data architectures
using
Azure Databricks
,
Azure Data Lake
, and
Azure Synapse Analytics
.
Develop and manage
ETL/ELT workflows
leveraging
Azure Data Factory
and Databricks notebooks.
Develop and optimize data models (both relational and dimensional) for analytical efficiency.
Work closely with data analysts, data scientists, and business stakeholders to understand data requirements.
Integrate data from diverse sources including APIs, databases, third-party platforms, and cloud storage.
Ensure data quality, consistency, and reliability through robust validation and monitoring frameworks.
Implement best practices for data security, governance, and compliance.
Optimize data storage and retrieval performance using modern data processing frameworks.
Contribute to the continuous improvement of data engineering standards and automation processes.
Use AI and machine learning techniques to automate data quality checks, anomaly detection, and issue resolution.

Ideal Candidate Profile

Bachelor s/Master s degree in Computer Science, Information Systems, Engineering, or a related field.
5+ years of experience as a Data Engineer or in a similar data-focused role.
Strong proficiency in SQL and experience with data modeling and database design (e.g., PostgreSQL, Snowflake, BigQuery, Redshift)
Hands-on experience with
Azure Databricks
,
Azure Data Factory
, and
Azure Data Lake Storage (ADLS)
.
Deep understanding of
data modeling, ETL design
, and
data warehousing
concepts.
Proven expertise with AWS data services : Glue, Redshift, S3, Athena, Lambda, Step Functions, and CloudWatch
Hands-on experience with ETL frameworks (e.g., Airflow, dbt, AWS Glue, Azure Data Factory).
Proficiency in Python or Scala for data processing and automation.
Experience with cloud platforms (AWS, Azure, or GCP) and related data services.
Familiarity with big data tools such as Spark, Hadoop, or Kafka.
Strong understanding of data warehousing concepts and best practices for data pipeline development.
Familiarity with DevOps practices , CI/CD for data workflows, and infrastructure-as-code tools (Terraform, CloudFormation)

Preferred Qualification

AWS certifications (e.g., AWS Certified Data Analytics Specialty , Solutions Architect ) are a plus.
Experience with containerization and orchestration tools (Docker, Kubernetes).
Knowledge of data governance, data cataloging, and metadata management.
Exposure to machine learning pipelines or real-time data streaming.
Strong problem-solving skills and ability to work in a fast-paced, agile environment.

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