Big Data Technical Architect

Hello,

"Big Data Architect"

Exp

Loc

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Notice Period:

NOTE: We are looking for Immediate joiners(notice period served or serving candidate)

Apply only If you are Immediate joiners(notice period served or serving candidate)

Apply only if you are having 10+Years of relevant experience as per the JD.

Big Data Technical Architect

Roles & Responsibilities

Key Responsibilities:

• • Architect and guide implementation of

  Data Lakes

  ,

  Lakehouses

  , and

  Data Warehouses

   using tools such as

  Snowflake

  ,

  Microsoft Fabric

  , and

  Delta Lake

  .
• • Design and implement scalable, secure, and high-performing

  Big Data architectures

   across

  AWS

   and

  Azure

  .
• • Develop robust

  ETL/ELT pipelines

   using modern data services like

  AWS Glue

  ,

  Azure Data Factory

  ,

  Spark

  , and custom scripts in

  Python/SQL/PLSQL

  .
• • Integrate structured and unstructured data sources using

  API integrations

  , event-driven pipelines,

  real-time data ingestion

  , and batch processing.
• • Lead the

  BI and analytics layer

   strategy using tools such as

  Tableau

  ,

  Power BI

  , and

  Qlik Sense

   for enterprise reporting and dashboarding.
• • Design and implement

  data models

   (conceptual, logical, physical) that support both operational and analytical requirements.
• • Establish and enforce

  data governance

  ,

  data security

  , and

  data quality

   standards across platforms.
• • Drive initiatives in

  data observability

  , monitoring data pipelines, identifying issues, and ensuring SLA adherence.
• • Serve as a

  technical SME and advisor

   to both internal teams and clientstranslating business needs into technical solutions.
• • Lead architectural reviews and provide guidance on data best practices and cloud optimization.
• • Develop and deliver

  technical presentations

   to executive and non-technical stakeholders.

Domain Experience (Good to Have):

• • Exposure to

  BFSI

   domain, including understanding of risk management, regulatory compliance (Basel III, PCI DSS), fraud detection, and financial data workflows.
• • Familiarity with

  Retail

   data challenges such as supply chain analytics, customer behavior tracking, inventory management, and omni-channel reporting.
• • Experience with

  Pharma

   and

  Healthcare

   sectors, including clinical data management, regulatory compliance (HIPAA, GDPR), patient analytics, and drug safety data.
• • Ability to adapt data architecture and BI solutions to domain-specific requirements across these industries, supporting both operational and strategic business goals.

Required Skills:

• • Bachelor of Engineering (B.E./B.Tech) degree in Computer Science, Information Technology, Electronics, or related field.
• • Strong hands-on experience with cloud platforms and related data technologies:
• o

  AWS:

   S3, AWS Glue, Redshift, Lambda, Kinesis Data Streams & Firehose, Managed Kafka (MSK), EMR (Spark), Athena, IAM, KMS.
• o

  Azure:

   Data Lake Storage Gen2, Synapse Analytics, Data Factory, Event Hubs, Stream Analytics, Managed Kafka, Databricks, Azure Functions, Active Directory, Key Vault.
• • Proven expertise in building and optimizing

  ETL/ELT pipelines

   using AWS Glue, Azure Data Factory, Apache Spark, and scripting languages like

  Python

  ,

  SQL

  , and

  PL/SQL

  .
• • Solid experience with

  data lake

   and

  lakehouse

   strategies, and hands-on with modern data warehouse platforms such as

  Snowflake

   and

  Microsoft Fabric

  .
• • Skilled in

  real-time data ingestion

   and streaming technologies like

  Apache Kafka

  ,

  AWS Kinesis

  ,

  Azure Event Hubs

  , and

  Spark Streaming

  .
• • Deep understanding of

  data modeling

   concepts (conceptual, logical, physical) and best practices for both OLTP and OLAP systems.
• • Expertise in

  business intelligence tools

   such as

  Tableau

  ,

  Power BI

  , and

  Qlik Sense

   for enterprise-grade dashboards and analytics.
• • Strong grasp of

  data governance

  ,

  data security

   (encryption, access control),

  data quality frameworks

  , and

  data observability

   tools like

  Monte Carlo

  ,

  DataDog

  , or

  Great Expectations

  .
• • Familiarity with relevant

  data privacy

   and

  regulatory compliance

   standards (GDPR, CCPA, HIPAA, PCI DSS).
• • Excellent

  client-facing communication

   skills with ability to explain complex technical concepts to non-technical stakeholders.
• • Proven leadership and mentoring capabilities in guiding cross-functional teams.

Qualifications:

• • Bachelor of Engineering (B.E./B.Tech) degree in Computer Science, Information Technology, Electronics, or related field.