Senior Data Engineer (AWS & Snowflake)

otelier.io

Ahmedabad, GJ, India2d ago

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Key details

Location
Ahmedabad, GJ, India
Work style
Onsite
Level
Senior
Experience
10–12 yrs
Function
Data & ML
Focus area
Data engineering & Analytics
Posted
2d ago

Skills

airflowawsbig dataci/cddata engineeringdata governancedata integrationdata modelingdata pipelinesdata qualitydbtdevopsemretlhadoopinfrastructure as codekafkakinesismetadata managementperformance optimizationperformance tuningpostgresqlpythonrbacredshifts3scalasnowflakesparksqlstakeholder managementworkflow orchestration

About the role

Description

  • Data Pipeline Development: Build and maintain efficient, scalable, and reliable pipelines to support analytics and reporting workloads.
  • Data Integration: Implement seamless integration across diverse data sources (structured, semi-structured, and unstructured) into Snowflake and AWS-based data platforms (Postgres/Aurora Postgres/Dynamo DB)
  • Data Governance: Establish and enforce data governance frameworks including metadata management, data lineage, data quality and data entitlement.
  • Cloud Engineering: Leverage AWS services (e.g., S3, Glue, Lambda, Redshift, EMR) to design cloud-native data solutions.
  • Performance Optimization: Monitor, troubleshoot and optimize data workflows for speed, scalability, and cost efficiency.
  • Collaboration: Partner with data architects, analysts and business stakeholders to translate requirements into technical solutions.
  • Best Practices: Drive adoption of engineering best practices, including CI/CD, automation, and Infrastructure-as-Code for data platforms.
  • Leveraging AI: Any experience in leveraging AI in execution or implementation of data pipelines and data integration solutions.

Requirements

  • 10–12 years of hands-on experience in data engineering.
  • Strong hands-on expertise in Snowflake data modelling, performance tuning, CDC, security and governance (Snowpipe, Dynamic Tables, DBT, Streams, RBAC).
  • Hands-on experience with AWS services (S3, Glue, Postgres, Redshift, EMR, IAM).
  • Proficiency in RDBMS concepts, SQL and programming languages such as Python or Scala.
  • Experience with ETL/ELT frameworks and workflow orchestration tools ( Snaplogic, Airflow, DBT).
  • Good understanding of data governance principles and implementation experience
  • Familiarity with DevOps practices and CI/CD pipelines for data engineering.
  • Excellent problem-solving, communication and stakeholder management skills.

Preferred Qualifications

  • Exposure to big data technologies (Spark, Hadoop).
  • Experience with real-time data streaming (Kafka, Kinesis).
  • Knowledge of data cataloging tools (Collibra, Alation).
  • Experience of using AI tools (Cloude, Cortex)
  • Prior experience in implementing enterprise-scale data modernization initiatives.

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