Data Architect

2 weeks ago

Bengaluru, Karnataka, India Bristlecone Full time
Specific Requirements at a Glance15 years of experience having architected multiple data solutions on

Google Cloud

primarily, like Data Warehouse, Data Lake, Data Lakehouse, etc. (experience in designing

Data Mesh

would be a huge plus)Good

data modeling

skills, having modelled Common Data Platforms for enterprisesUnderstanding of data integration / ETL / ELT pipelines having architected complex scenariosGood understanding of Data Governance concepts as they apply to a Data Lakehouse and BI architectureArchitecting solutions using

Databricks

(Unity Catalog, Delta Lake experience is a big plus) or

SnowflakeArchitecting solutions using

AWS stack or GCP

  • BigQuery, GCS, Dataproc, Dataplex, Pub-Sub, etc. (Dataplex experience would be a huge plus)Experience on other clouds would be appreciated; however, Google Cloud experience has to be primary
Job briefWe are looking for a Data Architect to build, optimize and maintain data lake architectures. The work includes Data Transformation using Cloud platforms and

Data Lakehouse

design and enhancement to better enable downstream BI applications using emerging technologies and standard Data Models.

We are looking for an experienced leader who herself / himself has utilized optimal methods to transform raw data into useful decision support systems to align with the business goals.

A detail-oriented person, with excellent organizational skills, who has strong analytical skills, and the ability to combine data from different sources.

Familiarity with several programming languages like Python, Scala, having worked on multiple cloud platforms and possessing knowledge of AI/ML technologies & algorithms and their applications.

An architect who has specifically designed Data Lakes on GCP while ensuring Metadata Management, operational cost reduction, data standardization, Data Governance Security, Scalability and Performance.

Primary Expectationsdata systems and pipelines upon evaluate business needs and objectivescomplex data analysis on raw source data and design data lake / model / storage to house it in a standardized mannerwith data scientists and architects on several projects and design solutions for use by the Data Science teamslead a team of 15+ developers, engineers, scientists to design complex data lake solutionson experience in developing ETL workflows and pipelines using

Apache Airflow , SAP BODS or similar toolsin working on cloud technologies

GCP / AWS / Azure


especially related to data & analyticson Big Data technologies especially, Spark, NoSQL, HDFSexpertise with data models and architecture, data migration and managing data qualityon and efficient in writing complex SQL queries for all test cases (Unit / System / functional / Data reconciliation / etc.)understanding of BI & DWH development methodologiesExperience with Data governance (Data Quality, Metadata Management, Security etc.)good knowledge of SAP ERP data , e.g., HR / Payroll / SuccessFactors, Finance, Procurement, etc.

Data Lake skills8 to 14 years of experience in the field of Data & Analytics, Cloud Data Management, Data Warehousing, least 3 years of experience working as a lead on a large-scale Data Lake implementationorganizational and time management with ability to manage multiple priorities to accomplish the objectives and goals anticipating and adjusting for problems and interruption / roadblocksunderstanding and experience practicing Agile and iterative software development methodologiesnumerical and analytical skillsTechnology Experience (AWS or GCP)AWS specific –Experience with AWS is a must and should have strong development experience in working with Lambda's/Cloud Functions, Cloud Storage / S3 Buckets, Compute Engine, EMR, RDS, Redshift / Athena, Glue / DataBrew / Step functions etc.

Data transfer between S3 / RedshiftData transfer between Data Factory / Synapse / SQLAirflow and / or other data orchestration platformsusing Python / PySpark, Scala, Java, etc.


GCP Specific –Big Query (must have)Excellent knowledge on RDBMS SQL / No SQL & BQ SQL conceptsHands on knowledge on writing complex SQL joins and operationsHands on knowledge on Stored procedure / Functions / Triggers etc.

Hands on knowledge on Dynamic SQL and code conversion.

Experience on writing cost effective Big Query SQL codeOther GCP Tools (should have worked on at least 2 from the list)Hands on knowledge using Database migration tasksHands on knowledge using Cloud functionHands on knowledge using Data Transfer ServicesHands on knowledge using DataprocHands on knowledge using Pub/SubHands on knowledge using Data FlowHands on knowledge managing GCS BucketsHands on knowledge working with Cloud ComposerCloud Data Fusion (good to have)Data Integration/Migration(JDBC) drivers with Cloud Data Fusion pipelines.

Multi-cloud integration (AWS / GCP / Azure)Knowledge of CDAP 6.8.0Data fusion governanceRealtime/Batch data integrationHands on REST APIs, time-based schedules, pipeline state-based triggers, logs, metrics.

Educational Qualificationsin Computer Science, IT, or similar field; a Master's is a plusArchitect / engineering certification (e.g., AWS / GCP certification) is a plus

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