Senior Data Engineer (AWS & Snowflake)Otelierfull-timeRequired skillsPythonAirflowRedshiftbig data technologiesdata pipelinedata solutionsDevOpsDynamo DBETLHadoopinfrastructure-as-codeKafkaLambdametadata managementPostgresSnowflakeSparkSQLAbout the role Otelier Website: otelier.io Job details: Job TypeFull-timeDescriptionData 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 QualificationsExposure 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. Click on Apply to know more. This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.