Key Roles and Responsibilities
Design, develop, and maintain scalable, secure, and high-performance data pipelines
using AWS, Snowflake, and Python.
Build end-to-end data engineering solutions, covering data ingestion, transformation,
validation, storage, and consumption layers.
Develop batch and real-time data integration frameworks to support business
reporting, analytics, and AI/ML use cases.
Create and optimize ELT/ETL processes to ensure productive data movement across
multiple source systems and cloud platforms.
Implement robust data quality frameworks and proactively identify, analyze, and
resolve data anomalies, inconsistencies, and performance issues.
Perform root cause analysis for data-related incidents and implement preventive
measures to improve platform reliability.
Design and optimize Snowflake data models, schemas, warehouses, and workloads
for performance and cost efficiency.
Develop reusable Python components, automation scripts, and frameworks to
improve engineering productivity and operational efficiency.
Collaborate with business, analytics, and technology teams to understand data
requirements and translate them into scalable technical solutions.
Implement monitoring, alerting, logging, and observability mechanisms for data
pipelines and platforms.
Follow and promote engineering best practices, including code reviews, version
control, CI/CD, automated testing, documentation, and secure development
standards.
Ensure adherence to data governance, security, compliance, and access control
requirements.
Continuously evaluate and adopt emerging technologies, tools, and best practices to




improve the overall data platform ecosystem.
Skills & Competencies
Technical Skills
Strong hands-on experience with AWS services such as S3, Lambda, Glue, Airflow,
EventBridge, IAM, and related cloud-native services.
Advanced proficiency in Snowflake, including procedures, data modeling,
performance tuning, Snowpipe, Streams, Tasks, Dynamic Tables, and security
frameworks.
Strong programming skills in Python with experience developing scalable data
processing frameworks and automation solutions.
Expertise in building and maintaining end-to-end data pipelines in cloud
environments.
Strong knowledge of SQL and database design principles.
Experience with data orchestration and workflow management tools such as Airflow
or equivalent.
Experience working with structured, semi-structured, and unstructured data.
Knowledge of data quality, data lineage, metadata management, and monitoring
practices.
Familiarity with API integrations, data lake architectures, and modern analytics
platforms.
Competencies
Strong analytical and problem-solving skills with the ability to identify and resolve
complex data issues.
Proven ability to detect, investigate, and remediate data anomalies and quality
concerns.
Strong understanding of scalable architecture and data engineering design patterns.
Commitment to coding standards, development best practices, and documentation.
Excellent stakeholder communication and collaboration skills.
Ability to work independently in a fast-paced, agile environment.
Continuous learning mindset with a focus on innovation and operational excellence.
Strong ownership, accountability, and attention to detail

📌 AWS Snowflake Engineer (Mumbai)
🏢 TRIGENT SOFTWARE PRIVATE
📍 Mumbai