GCP Data Engineer

4 weeks ago

delhi, India EXL Full time
Position – GCP Data Engineer – Senior
Work Location – Hybrid – all EXL locations. Will involve relocation for selected outstation candidates.
Experience - 5 to 8 Years
Must Have:
5+ years of proven experience in Big Data Engineering .
Mandatory Technical Proficiency - Hands-on experience with Python , PySpark , Google Cloud Full Stack , SQL, Could run (Docker), DevOps , Databricks , DBT & Terraform .
Experience with Google Cloud Services such as Streaming +Batch, Cloud Storage, Cloud Dataflow, Data Proc, Big Query & Big Table
Proven real-time exposure and use of contemporary data mining, cloud computing, and data management ecosystems like Google Cloud, Pub/Sub, Cloud Shell, Hadoop, HDFS, and Spark.
Proficient in Data Modelling that can represent complex data structures while ensuring accuracy, consistency, and efficiency; data warehousing , and ETL processes .
Ability to perform system analysis and assessment of existing Systems Design and operating methodologies leveraging in-depth knowledge of big data technologies and ecosystems.
Experience with GitHub, Anaplan, Looker & Power BI,
Excellent problem-solving skills and the ability to address complex technical challenges.
Strong communication skills.
Good To Have:
Experience with Apigee, Apollo GraphQL.
Experience with Quality Assurance, Agile , Documentation & Presentation.
Experience with serverless Data warehousing concepts,
Knowledge of Snowflake , ML - Machine Learning, Gen AI (LLMs), Marketing activation.
Role & Responsibilities:
Data ingestion & cleansing from sources systems (files, DBs, APIs)
Harmonize, integrate, and centralize data to BigQuery , Data warehouse
Calculations, derivations, and aggregations in BigQuery , Data mart
Integrate with Master Data Services , automate data quality rules
Data exposition ( API ) with data-as-a-service
Automate deployments and facilitate MTQ/MTP through CI-CD/DevOps
Conduct code reviews, automate regression tests, facilitate data reloads
To be upskilled if not qualify: DBT , Terraform , Databricks
Streamline workflows and orchestrate Data pipelines
Conduct code reviews, automate regression tests, and facilitate data reloads.
Participate in requirements gathering and architectural discussions.
Responsible for the Overall Quality of Engineering builds.
Programming Hands-on: Develop and maintain software components using Python , PySpark , and GCP services to process and analyze large datasets efficiently. Build data pipelines and perform data transformations.
Enforce consistent standards and quality through end-to-end review of all artifacts (incl. BRD, HLD, LLD, Data Models, STTMs, UI-UX, NFRs, Code, Test, PBI architecture design)
POC and Pilot of new reusable frameworks, tools & technologies.
Evaluate the newest technologies for optimization opportunities and future enhancement needs like self-serve and ad hoc reporting. Implement necessary infrastructure for optimal and efficient ETL from disparate data.
Performance Optimization : Identify and address performance bottlenecks, ensuring the system meets required throughput and latency targets.
Security and Compliance : Ensure data solutions adhere to security and compliance standards, implementing necessary controls and encryption mechanisms.
Documentation : Create and maintain comprehensive technical documentation to support the development and maintenance of data solutions.

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