Associate Principal - Data Sciences

Job Title : Data Architect

Certification Required Databricks Certified Associate Developer for Apache Spark

Job Summary

We are seeking a skilled PySpark Developer to design develop and optimize largescale data processing solutions using Apache Spark and Python The ideal candidate will have experience building ETL pipelines handling big data workloads and working with cloudbased data platforms to support analytics reporting and data engineering initiatives

Key Responsibilities

Design develop and maintain scalable data pipelines using PySpark

Build and optimize ETLELT processes for structured and unstructured data

Process large datasets using Apache Spark in distributed environments

Collaborate with business analysts data architects and data scientists to understand data requirements

Integrate data from multiple sources including databases APIs and cloud storage

Perform data cleansing transformation and validation activities

Optimize Spark jobs for performance scalability and resource utilization

Develop data quality checks and monitoring mechanisms

Troubleshoot production issues and provide timely resolutions

Implement best practices for coding testing deployment and documentation

Work with cloud platforms such as AWS Azure or GCP for data engineering solutions

Participate in code reviews and ensure adherence to development standards

Required Skills

Strong experience in Python and PySpark development

Handson experience with Apache Spark Spark SQL DataFrames and Spark Streaming

Strong knowledge of SQL and relational databases

Experience with ETL development and data warehousing concepts

Familiarity with Hadoop ecosystem technologies HDFS Hive Yarn

Experience with version control systems such as Git

Understanding of distributed computing concepts and performance tuning

Knowledge of workflow orchestration tools such as Airflow Oozie or Azure Data Factory

Strong analytical and problemsolving skills

Preferred Skills

Experience with cloud platforms AWS EMR Azure Databricks Azure Synapse GCP Dataproc

Exposure to Delta Lake Iceberg or Lakehouse architectures

Experience with Kafka or other realtime streaming solutions

Knowledge of CICD pipelines and DevOps practices

Understanding of data governance security and compliance requirements

Qualifications

Bachelors or Masters degree in Computer Science Information Technology Engineering or a related field

58 years of experience in Data Engineering or Big Data development

Relevant certifications in Spark Databricks Azure AWS or GCP are an added advantage

NicetoHave Technologies

Databricks

Azure Data Factory ADF

Azure Synapse Analytics

AWS Glue

Kafka

Delta Lake

Hive

Airflow

Snowflake

Sample Experience Requirement

11 years of experience in Data Engineering

11 years of handson experience with PySpark development

Experience designing and supporting enterprisescale data platforms

Proven ability to optimize Spark applications for highvolume data processing

Key Competencies

Communication and stakeholder management

Problemsolving and analytical thinking

Team collaboration

Attention to detail

Ownership and accountability

This JD can be used for Data Engineer PySpark Senior PySpark Developer or PySpark Lead roles with minor modifications to experience and leadership expectations