Data Architect

Lancesoft; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Lancesoft is seeking a senior data engineer to architect and deliver scalable data infrastructure on the Azure cloud. You will design data ingestion, processing and transformation pipelines and work with data scientists, managers and engineers in a Scrum/Agile setup.

Responsibilities include mentoring the team, aligning with security and compliance standards, and delivering robust CI/CD pipelines. 8–12 years of relevant experience is expected.

Qualifications

• Bachelor or higher degree in computer science, engineering, information systems or other quantitative fields.
• 8 to 12 years relevant experience.
• Hands on experience with Spark for data processing (batch and/or real-time).
• Configuring Delta Lake on Azure Databricks.
• Languages: SQL, PySpark, Python.
• Cloud platforms: Azure.
• Azure Data Factory, Azure Data Lake, Azure SQL DB, Synapse, SQL Pools, Databricks.
• Designing data solutions in Azure incl. data distributions and partitions, scalability, cost-management, disaster recovery and high availability.
• Azure DevOps (or similar) for source control and CI/CD pipelines.
• Experience designing and implementing large-scale distributed systems.
• Customer management and leadership through influence.

Responsibilities

• Designs, implements and maintains reliable and scalable data infrastructure
• Writes, deploys and maintains software to build, integrate, manage, maintain, and quality-assure data
• Designs, develops, and delivers large-scale data ingestion, data processing, and data transformation projects on the Azure cloud
• Mentors and shares knowledge with the team to provide design reviews, discussions and prototypes
• Works with customers to deploy, manage, and audit standard processes for cloud products
• Adheres to and advocates for software & data engineering standard processes (e.g. technical design and review, unit testing, monitoring, alerting, source control, code review & documentation)
• Deploys secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline
• Service reliability and following site-reliability engineering standard processes: on-call rotations for services they maintain, responsible for defining and maintaining SLAs. Designs, builds, deploys and maintains infrastructure as code. Containerizes server deployments.
• Part of a cross-disciplinary team working closely with other data engineers, software engineers, data scientists, data managers and business partners in a Scrum/Agile setup

Skills

Databricks

ADF

Spark

SQL

PySpark

Spark-SQL

Education

Bachelor’s or higher in CS/Engineering/IS

Tools

Azure

Azure Databricks

Azure Data Factory

Azure Synapse

Azure SQL DB

Power BI

Job description

Responsibilities:

Job Description:

Key Responsibilities:

• Designs, implements and maintains reliable and scalable data infrastructure
• Writes, deploys and maintains software to build, integrate, manage, maintain, and quality-assure data
• Designs, develops, and delivers large-scale data ingestion, data processing, and data transformation projects on the Azure cloud
• Mentors and shares knowledge with the team to provide design reviews, discussions and prototypes
• Works with customers to deploy, manage, and audit standard processes for cloud products
• Adheres to and advocates for software & data engineering standard processes (e.g. technical design and review, unit testing, monitoring, alerting, source control, code review & documentation)
• Deploys secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline
• Service reliability and following site-reliability engineering standard processes: on-call rotations for services they maintain, responsible for defining and maintaining SLAs. Designs, builds, deploys and maintains infrastructure as code. Containerizes server deployments.
• Part of a cross-disciplinary team working closely with other data engineers, software engineers, data scientists, data managers and business partners in a Scrum/Agile setup

Job Requirements:

Education :

Bachelor or higher degree in computer science, Engineering, Information Systems or other quantitative fields

Experience :

1) Years of experience: 8 to 12 years relevant experience

2) Deep and hands-on experience designing, planning, productionizing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments

3) Hands on experience with:

a) Spark for data processing (batch and/or real-time)

b) Configuring Delta Lake on Azure Databricks

c) Languages: SQL, pyspark, python

d) Cloud platforms: Azure

e) Azure Data Factory (must) , Azure Data Lake (must), Azure SQL DB (must), Synapse (must), SQL Pools (must), Databricks (must)

f) Designing data solutions in Azure incl. data distributions and partitions, scalability, cost-management, disaster recovery and high availability

g) Azure Devops (or similar tools) for source control & building CI/CD pipelines

4) Experience designing and implementing large-scale distributed systems

5) Customer management and front-ending and ability to lead large organizations through influence

Desirable Criteria :

• Strong customer management- own the delivery for Data track with customer stakeholders
• Continuous learning and improvement attitude

Key Behaviors :

• Empathetic: Cares about our people, our community and our planet
• Curious: Seeks to explore and excel
• Creative: Imagines the extraordinary
• Inclusive: Brings out the best in each other

Mandatory skill sets:

Must have’ knowledge, skills and experiences

Databricks, ADF, spark, SQL, pyspark, spark-SQL

Preferred skill sets:

‘Good to have’ knowledge, skills and experiences

Cosmos DB, Data modeling, Synapse, PowerBI, experience of having built analytics solution with SAP as data source for ingestion pipelines.

Depth:

Candidate should have in-depth hands-on experience w.r.t end to end solution designing in Azure data lake, ADF pipeline development and debugging, various file formats, Synapse and Databricks with excellent coding skills in PySpark and SQL with logic building capabilities. He/she should have sound knowledge of optimizing workloads.

Years of experience required:

8 to 12 years relevant experience

Preferred candidate profile