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TechMynd Consulting
TechMynd Consulting cover picture
Founded :
2024
Type :
Services
Size :
0-20
Stage :
Bootstrapped

About

At TechMynd Consulting, we specialize in business consulting, recruitment, and strategic talent solutions, helping top professionals connect with the right opportunities. Our growing network of industry leaders and innovative organizations allows us to bridge the gap between talent and business success.

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Tech stack

Human Resources (HR)
Staffing

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business consulting, recruitment, and strategic talent solutions, helping top professionals connect with the right opportunities.

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Jobs at TechMynd Consulting

TechMynd Consulting
at TechMynd Consulting
2 candid answers
Suraj N
Posted by Suraj N
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

Bengaluru (Bangalore), Gurugram, Mumbai
4 - 8 yrs
₹10L - ₹24L / yr
skill iconData Science
skill iconPostgreSQL
skill iconPython
Apache
skill iconAmazon Web Services (AWS)
+5 more

Senior Data Engineer


Location: Bangalore, Gurugram (Hybrid)


Experience: 4-8 Years


Type: Full Time | Permanent


Job Summary:


We are looking for a results-driven Senior Data Engineer to join our engineering team. The ideal candidate will have hands-on expertise in data pipeline development, cloud infrastructure, and BI support, with a strong command of modern data stacks. You’ll be responsible for building scalable ETL/ELT workflows, managing data lakes and marts, and enabling seamless data delivery to analytics and business intelligence teams.


This role requires deep technical know-how in PostgreSQL, Python scripting, Apache Airflow, AWS or other cloud environments, and a working knowledge of modern data and BI tools.


Key Responsibilities:


PostgreSQL & Data Modeling


· Design and optimize complex SQL queries, stored procedures, and indexes


· Perform performance tuning and query plan analysis


· Contribute to schema design and data normalization


Data Migration & Transformation


· Migrate data from multiple sources to cloud or ODS platforms


· Design schema mapping and implement transformation logic


· Ensure consistency, integrity, and accuracy in migrated data


Python Scripting for Data Engineering


· Build automation scripts for data ingestion, cleansing, and transformation


· Handle file formats (JSON, CSV, XML), REST APIs, cloud SDKs (e.g., Boto3)


· Maintain reusable script modules for operational pipelines


Data Orchestration with Apache Airflow


· Develop and manage DAGs for batch/stream workflows


· Implement retries, task dependencies, notifications, and failure handling


· Integrate Airflow with cloud services, data lakes, and data warehouses


Cloud Platforms (AWS / Azure / GCP)


· Manage data storage (S3, GCS, Blob), compute services, and data pipelines


· Set up permissions, IAM roles, encryption, and logging for security


· Monitor and optimize cost and performance of cloud-based data operations


Data Marts & Analytics Layer


· Design and manage data marts using dimensional models


· Build star/snowflake schemas to support BI and self-serve analytics


· Enable incremental load strategies and partitioning


Modern Data Stack Integration


· Work with tools like DBT, Fivetran, Redshift, Snowflake, BigQuery, or Kafka


· Support modular pipeline design and metadata-driven frameworks


· Ensure high availability and scalability of the stack


BI & Reporting Tools (Power BI / Superset / Supertech)


· Collaborate with BI teams to design datasets and optimize queries


· Support development of dashboards and reporting layers


· Manage access, data refreshes, and performance for BI tools




Required Skills & Qualifications:


· 4–6 years of hands-on experience in data engineering roles


· Strong SQL skills in PostgreSQL (tuning, complex joins, procedures)


· Advanced Python scripting skills for automation and ETL


· Proven experience with Apache Airflow (custom DAGs, error handling)


· Solid understanding of cloud architecture (especially AWS)


· Experience with data marts and dimensional data modeling


· Exposure to modern data stack tools (DBT, Kafka, Snowflake, etc.)


· Familiarity with BI tools like Power BI, Apache Superset, or Supertech BI


· Version control (Git) and CI/CD pipeline knowledge is a plus


· Excellent problem-solving and communication skills

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