Senior Data Engineer

2 weeks ago


South Moti Bagh, India TGS The Global Skills Full time

Responsibilities :


- Hands on experience in data related activities such as data parsing, cleansing quality definition data pipelines, storage and ETL scripts.


- Expert knowledge in AWS Data Lake implementation and support (S3, Glue, DMS Athena, Lambda, API Gateway, Redshift).


- Experiences in programming language Experience with data migration with hands-on experience.


- Experiences in consuming rest API using various authentication options with in AWS.


- Lambda architecture.


- Orchestrate triggers, debug and schedule batch job using a AWS Glue, Lambda and step functions.


- Hands-on experience with Redshift, including data models, storage, and writing effective queries.


- Understanding of AWS security features such as IAM roles and policies.


- Knowledge of the Devops tools and CI/CD process.


- AWS certification in AWS is highly Skills & Expertise :


Cloud (AWS) Expertise :


- S3 (Simple Storage Service) : Data storage and partitioning, lifecycle policies, data replication, encryption at rest and transit, and data versioning, Data archive and Data sharing mechanisms.


- Lambda : Creation of Lambdas, configuring event-driven functions, monitoring, and integration with other AWS services of s3,Glue,API Gateway, Redshift etc.


- Glue : Creating & Managing ETL pipelines, Glue crawlers, job scheduling, and integration with S3, Redshift, and Athena.


- Redshift : Creating Tables, Views and Stored procedures, parameter tuning, workload management, configuring triggers, Redshift Spectrum usage for querying S3 data.


- API Gateway : Designing Restful APIs, securing endpoints using IAM or Cognito, throttling and logging API usage.


- VPC (Virtual Private Cloud) : Aware of existing VPC design, subnets, NAT gateways, peering, routing, and network ACLs for services creation.


- ELB (Elastic Load Balancer) : Configuring ALB/NLB for load distribution, health checks, sticky sessions, and SSL termination.


- CloudTrail : Enabling auditing and compliance logging, managing trails, integrating with CloudWatch and third-party SIEM tools.


- SageMaker : Knowledge about Sagemaker ML model training and deployment workflows, managing notebooks, endpoints, and model & DevOps Tools :


- GitHub / GitHub Actions : Managing version control, branching strategies, and automating workflows for testing and deployment.


- Jenkins / CloudBees : Building pipelines for build-test-deploy automation, plugin management, parallel execution, and integrations with SCM and artifact repositories.


- SonarQube : Static code analysis, security vulnerability checks, technical debt reporting, integration into & AI/ML Awareness :


- Understanding of ML model lifecycle : data preprocessing, training, evaluation, deployment, and monitoring.


- Experience supporting Data Scientists and ML Engineers in deploying models to production.


- Familiarity with tools and workflows like SageMaker, MLflow, Airflow (optional), and pipelines Skills :


AWS Data Lake, Python/PySpark, SQL, AWS Lambda, Redshift, AWS Glue, Data Migration, IAM Security, CI/CD, AWS Certification.


(ref:hirist.tech)
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