Data Engineer

Job Title: Senior Data Engineer / Analytics Engineer

Experience

8+ Years

Location

Flexible / Hybrid / Remote

Job Summary

We are seeking an experienced Senior Data Engineer / Analytics Engineer with 8+ years of hands-on experience in designing, building, and optimizing scalable data platforms and analytics solutions. The ideal candidate should possess strong expertise in SQL, dbt, AWS, and Python, along with excellent communication and stakeholder management skills. The role involves working closely with business teams, data analysts, architects, and engineering teams to deliver reliable and scalable data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and manage data transformation frameworks using dbt.
• Develop high-performance data models and optimize complex SQL queries.
• Implement data ingestion and integration processes from multiple data sources.
• Leverage AWS services to build cloud-native data solutions.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with business stakeholders to understand requirements and convert them into technical solutions.
• Create reusable data models, documentation, and best practices.
• Monitor and troubleshoot production data pipelines to ensure reliability and performance.
• Mentor junior team members and participate in code reviews and architectural discussions.
• Support BI and reporting initiatives by providing curated and trusted datasets.

Required Skills

SQL

• Advanced SQL development and performance tuning.
• Expertise in data modeling, query optimization, and database design.
• Experience working with large-scale relational and analytical databases.

dbt

• Strong experience in developing and maintaining dbt projects.
• Creating incremental models, snapshots, tests, macros, and documentation.
• Understanding of CI/CD integration and deployment practices for dbt.

AWS

Hands-on experience with:

• Amazon S3
• AWS Glue
• AWS Lambda
• Amazon Redshift
• AWS Athena
• IAM and Security Best Practices
• CloudWatch Monitoring
• EventBridge / Step Functions (preferred)

Python

• Strong development experience using Python for data engineering and automation.
• Expertise with Pandas, NumPy, and API integrations.
• Experience building scalable data processing frameworks.

Additional Technical Skills

• Experience with ETL/ELT frameworks.
• Knowledge of data warehousing concepts and dimensional modeling.
• Exposure to CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
• Experience with Airflow or other workflow orchestration tools is preferred.
• Familiarity with Agile/Scrum methodologies.

Soft Skills

• Strong verbal and written communication skills.
• Ability to interact confidently with business stakeholders and leadership teams.
• Excellent problem-solving and analytical thinking capabilities.
• Experience leading technical discussions and solution design workshops.
• Strong collaboration and mentoring skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
• AWS Certification (Associate or Professional level) preferred.
• Experience in modern cloud data platforms and analytics ecosystems.

Nice to Have

• Snowflake
• Databricks
• Power BI or Tableau
• Data Governance and Data Quality frameworks
• Infrastructure as Code (Terraform/CloudFormation)

Job Title: Senior Data Engineer / Analytics Engineer

Experience

8+ Years

Location

Flexible / Hybrid / Remote

Job Summary

We are seeking an experienced Senior Data Engineer / Analytics Engineer with 8+ years of hands-on experience in designing, building, and optimizing scalable data platforms and analytics solutions. The ideal candidate should possess strong expertise in SQL, dbt, AWS, and Python, along with excellent communication and stakeholder management skills. The role involves working closely with business teams, data analysts, architects, and engineering teams to deliver reliable and scalable data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and manage data transformation frameworks using dbt.
• Develop high-performance data models and optimize complex SQL queries.
• Implement data ingestion and integration processes from multiple data sources.
• Leverage AWS services to build cloud-native data solutions.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with business stakeholders to understand requirements and convert them into technical solutions.
• Create reusable data models, documentation, and best practices.
• Monitor and troubleshoot production data pipelines to ensure reliability and performance.
• Mentor junior team members and participate in code reviews and architectural discussions.
• Support BI and reporting initiatives by providing curated and trusted datasets.

Required Skills

SQL

• Advanced SQL development and performance tuning.
• Expertise in data modeling, query optimization, and database design.
• Experience working with large-scale relational and analytical databases.

dbt

• Strong experience in developing and maintaining dbt projects.
• Creating incremental models, snapshots, tests, macros, and documentation.
• Understanding of CI/CD integration and deployment practices for dbt.

AWS

Hands-on experience with:

• Amazon S3
• AWS Glue
• AWS Lambda
• Amazon Redshift
• AWS Athena
• IAM and Security Best Practices
• CloudWatch Monitoring
• EventBridge / Step Functions (preferred)

Python

• Strong development experience using Python for data engineering and automation.
• Expertise with Pandas, NumPy, and API integrations.
• Experience building scalable data processing frameworks.

Additional Technical Skills

• Experience with ETL/ELT frameworks.
• Knowledge of data warehousing concepts and dimensional modeling.
• Exposure to CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
• Experience with Airflow or other workflow orchestration tools is preferred.
• Familiarity with Agile/Scrum methodologies.

Soft Skills

• Strong verbal and written communication skills.
• Ability to interact confidently with business stakeholders and leadership teams.
• Excellent problem-solving and analytical thinking capabilities.
• Experience leading technical discussions and solution design workshops.
• Strong collaboration and mentoring skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
• AWS Certification (Associate or Professional level) preferred.
• Experience in modern cloud data platforms and analytics ecosystems.

Nice to Have

• Snowflake
• Databricks
• Power BI or Tableau
• Data Governance and Data Quality frameworks
• Infrastructure as Code (Terraform/CloudFormation)

Job Title: Senior Data Engineer / Analytics Engineer

Experience

8+ Years

Location

Flexible / Hybrid / Remote

Job Summary

We are seeking an experienced Senior Data Engineer / Analytics Engineer with 8+ years of hands-on experience in designing, building, and optimizing scalable data platforms and analytics solutions. The ideal candidate should possess strong expertise in SQL, dbt, AWS, and Python, along with excellent communication and stakeholder management skills. The role involves working closely with business teams, data analysts, architects, and engineering teams to deliver reliable and scalable data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and manage data transformation frameworks using dbt.
• Develop high-performance data models and optimize complex SQL queries.
• Implement data ingestion and integration processes from multiple data sources.
• Leverage AWS services to build cloud-native data solutions.
• Ensure data quality, governance, security, and compliance across data platforms.
• Collaborate with business stakeholders to understand requirements and convert them into technical solutions.
• Create reusable data models, documentation, and best practices.
• Monitor and troubleshoot production data pipelines to ensure reliability and performance.
• Mentor junior team members and participate in code reviews and architectural discussions.
• Support BI and reporting initiatives by providing curated and trusted datasets.

Required Skills

SQL

• Advanced SQL development and performance tuning.
• Expertise in data modeling, query optimization, and database design.
• Experience working with large-scale relational and analytical databases.

dbt

• Strong experience in developing and maintaining dbt projects.
• Creating incremental models, snapshots, tests, macros, and documentation.
• Understanding of CI/CD integration and deployment practices for dbt.

AWS

Hands-on experience with:

• Amazon S3
• AWS Glue
• AWS Lambda
• Amazon Redshift
• AWS Athena
• IAM and Security Best Practices
• CloudWatch Monitoring
• EventBridge / Step Functions (preferred)

Python

• Strong development experience using Python for data engineering and automation.
• Expertise with Pandas, NumPy, and API integrations.
• Experience building scalable data processing frameworks.

Additional Technical Skills

• Experience with ETL/ELT frameworks.
• Knowledge of data warehousing concepts and dimensional modeling.
• Exposure to CI/CD tools such as GitHub Actions, Jenkins, or Azure DevOps.
• Experience with Airflow or other workflow orchestration tools is preferred.
• Familiarity with Agile/Scrum methodologies.

Soft Skills

• Strong verbal and written communication skills.
• Ability to interact confidently with business stakeholders and leadership teams.
• Excellent problem-solving and analytical thinking capabilities.
• Experience leading technical discussions and solution design workshops.
• Strong collaboration and mentoring skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related field.
• AWS Certification (Associate or Professional level) preferred.
• Experience in modern cloud data platforms and analytics ecosystems.

Nice to Have

• Snowflake
• Databricks
• Power BI or Tableau
• Data Governance and Data Quality frameworks
• Infrastructure as Code (Terraform/CloudFormation)