Data Engineer at Adsremedy Media LLP · Remote, Mumbai · 1 - 3 years · ₹3L - ₹10L / yr · Bootstrapped · Remote friendly · Posted 6 Apr 2026
About the Role:
We are seeking a skilled Data Engineer to join our growing AdTech team. In this role, you will design, build, and maintain high-performance ETL pipelines and large-scale data processing systems. You will work with massive datasets and distributed frameworks to power Adsremedy’s data-driven advertising solutions across Programmatic, In-App, CTV, and DOOH platforms.
What You’ll Do:
- Design, develop, and maintain scalable ETL pipelines on self-managed infrastructure
- Process and optimize large-scale datasets (terabytes of data) with high reliability and performance
- Build robust data processing workflows using Apache Spark (preferred) and/or Apache Flink
- Integrate, clean, and transform data from multiple internal and external sources
- Partner closely with data scientists, analysts, and business stakeholders to enable actionable insights
- Monitor, troubleshoot, and optimize data pipelines for operational excellence
- Ensure data quality, consistency, and performance across all data workflows
- Participate in code reviews and uphold best practices in data engineering
- Collaborate with QA teams to deliver production-ready, reliable systems
- Mentor junior engineers and promote knowledge sharing within the team
- Stay current with emerging data engineering tools, frameworks, and industry trends
What You’ll Need:
- 2+ years of experience building ETL pipelines using Apache Spark and/or Apache Flink
- Hands-on experience with big data caching solutions such as ScyllaDB, Aerospike, or similar
- Strong understanding of data lake architectures and tools like Delta Lake
- Proven experience handling terabytes of data in distributed environments
- Proficiency in Scala, Python, or Java
- Experience working with cloud data platforms (AWS S3, Azure Data Lake, Google BigQuery)
- Strong knowledge of SQL, data modeling, and data warehousing concepts
- Familiarity with Git and CI/CD workflows
- Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment
Nice to Have
- Experience with Apache Kafka for real-time data streaming
- Familiarity with Apache Airflow or similar orchestration tools
Shubham Vishwakarma
Full Stack Developer - Averlon
About Adsremedy Media LLP
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Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Python, Hadoop, and Apache Spark.
- Develop efficient data processing and transformation workflows for large datasets.
- Write, optimize, and maintain complex SQL queries and PL/SQL procedures.
- Perform data extraction, transformation, and loading (ETL) from multiple data sources.
- Work with structured and unstructured data to support analytics and reporting requirements.
- Optimize data pipelines and queries for performance, scalability, and reliability.
- Ensure data quality, consistency, security, and integrity across data platforms.
- Collaborate with cross-functional teams to understand business requirements and deliver data engineering solutions.
- Use Git, automation, and CI/CD practices to support development and deployment.
Required Skills
- 4.5–10 years of experience in software development or data engineering.
- Strong proficiency in AWS
- Hands-on experience with Hadoop and Apache Spark.
- Good knowledge of SQL and PL/SQL, including query optimization and stored procedures.
- Experience in ETL development, data processing, and data pipeline design.
- Understanding of data warehousing concepts and distributed computing.
- Strong problem-solving, debugging, and performance-tuning skills.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Data Engineer Hiring Post
🚨 Hiring: Data Engineer | PySpark + Python + SQL
We are looking for experienced Data Engineers to join our team!
🔹 Experience: 5 to 9 Years
🔹 Locations: Bangalore / Hyderabad
🔹 Interview Process:
• 1st Round – Virtual
• 2nd Round – Face-to-Face (Karat Test)
🔑 Key Skills:
✅ PySpark
✅ SQL
✅ Python
✅ ETL
📩 Interested candidates can share their updated resume.
#Hiring #DataEngineer #PySpark #Python #SQL #ETL #BangaloreJobs #HyderabadJobs #TechHiring #ImmediateHiring
1st virtual , 2nd round F2F -
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
Bang/hyderabad
immediate to 15days.
Responsibilities and JD
Job Description: We are looking for a Senior Developer with strong expertise in PySpark, Databricks, and Snowflake to build scalable data engineering solutions and enterprise data platforms.
Key Responsibilities:
- Design, develop, and maintain ETL/ELT pipelines using PySpark, Databricks, and Snowflake.
- Develop batch and real-time data processing solutions for structured and semi-structured data.
- Build and optimize Databricks notebooks, workflows, and Delta Lake solutions.
- Design and implement Snowflake databases, schemas, views, stored procedures, tasks, and streams.
- Develop scalable data models, data marts, and data warehouse solutions.
- Optimize PySpark jobs, Databricks workloads, and Snowflake queries for performance and cost efficiency.
- Implement data quality, validation, governance, and security controls.
- Collaborate with business stakeholders, architects, and cross-functional teams to deliver data solutions.
- Manage source control and CI/CD deployments using Git and Azure DevOps.
- Troubleshoot production issues, perform root cause analysis, and ensure pipeline reliability.
- Mentor junior team members and participate in code reviews and technical design discussions.
Required Skills: PySpark, Databricks, Snowflake, Python, SQL.
Experience: 5+ years of Data Engineering experience with strong hands-on expertise in PySpark, Databricks, and Snowflake.
role: data engineer
Python pyspark, SQL, data engineer
5+yrs
Bangalore/Hyderabad
immediate to 15days.
1st virtual , 2nd round F2F
Python pyspark, SQL, data engineer
5+yrs
9+yrs
Bangalore/Hyderabad
immediate to 15days.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and PySpark.
- Work extensively with Databricks and Delta Lake, including Delta tables, MERGE operations, schema evolution, Time Travel, and data optimization.
- Develop, schedule, and monitor Apache Airflow DAGs for workflow orchestration and dependency management.
- Work with Kubernetes for containerized application deployment, orchestration, monitoring, and troubleshooting.
- Develop reusable and optimized Python code following software engineering best practices.
- Optimize Spark jobs for performance, scalability, and cost efficiency.
- Implement data quality checks, error handling, logging, and monitoring mechanisms.
- Use Git for version control, branching, pull requests, code reviews, and collaborative development.
- Troubleshoot pipeline failures, investigate data issues, and implement reliable solutions.
- Collaborate with cross-functional teams to understand business requirements and deliver efficient data solutions.
Required Technical Skills
- Python: Strong programming skills, including data manipulation, exception handling, modular programming, and debugging.
- PySpark: Hands-on experience with Spark DataFrames, Spark SQL, joins, transformations, partitioning, and performance tuning.
- Databricks: Strong understanding of Databricks architecture, notebooks, workflows, compute management, and job execution.
- Delta Lake: Experience with Delta tables, ACID transactions, MERGE/UPSERT, schema enforcement, schema evolution, VACUUM, and Time Travel.
- Apache Airflow: Experience developing DAGs, managing task dependencies, configuring retries, scheduling workflows, and troubleshooting failures.
- Kubernetes: Practical knowledge of pods, deployments, services, ConfigMaps, Secrets, resource management, and troubleshooting containerized workloads.
- Git: Proficiency in branching strategies, pull requests, merging, and resolving conflicts.
- SQL: Strong SQL skills, including complex joins, CTEs, window functions, and query optimization.
Good to Have
- Experience with Docker and containerization best practices.
- Experience with Databricks Unity Catalog and data governance.
- Knowledge of CI/CD pipelines and automated deployments.
- Experience deploying and managing Airflow workloads on Kubernetes.
- Familiarity with Kubernetes monitoring, autoscaling, and resource optimization.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Understanding of data lakehouse architecture and data modeling.
- Experience with batch and incremental data processing.
- Familiarity with data quality frameworks and automated testing.
Preferred Candidate Profile
- Strong analytical and problem-solving skills.
- Ability to independently design, develop, deploy, and troubleshoot data pipelines.
- Good understanding of distributed data processing and container orchestration.
- Experience working in an Agile development environment.
- Strong communication and collaboration skills.
About Solutionara
Solutionara is an AI-led IT Consulting and Technology Services organization delivering enterprise transformation through Cloud, Integration, Data Engineering, Digital Experience, AI, and Enterprise Applications.
Headquartered in the United States with a Global Delivery Center (GDC) in Noida, India, Solutionara partners with enterprise organizations across retail, manufacturing, distribution, consumer goods, and other industries to design, implement, and support scalable technology solutions.
As a rapidly growing consulting organization, we foster a culture of ownership, innovation, collaboration, and continuous improvement, empowering our teams to contribute beyond their immediate responsibilities while delivering exceptional value to our global clients.
Every team member is expected to think like a consultant and business problem solver—understanding client objectives, challenging assumptions when appropriate, leveraging AI responsibly, and continuously identifying opportunities to improve quality, productivity, and customer outcomes.
AI is embedded into how we work, but it is an enabler—not a replacement for expertise, critical thinking, or accountability.
Role Overview
Solutionara is seeking a Senior Data Engineer with strong data engineering and database expertise to design, build, optimize, and support enterprise-scale data solutions.
This is a hands-on engineering position requiring strong SQL, Python, ETL/ELT, database, cloud, and troubleshooting capabilities. The engineer will work closely with technical leads and client stakeholders while taking ownership of major engineering components.
Location: Noida, India – Onsite | Employment Type: Full-Time | Experience: 6–9 Years
Key Responsibilities
Data Engineering
- Design, develop, test, deploy, and support scalable ETL/ELT pipelines.
- Build ingestion and transformation solutions across databases, APIs, files, and enterprise applications.
- Develop high-quality SQL and Python-based data processing solutions.
- Implement batch and incremental data-processing patterns.
- Develop reusable engineering components and frameworks.
- Support complex data migration and transformation activities.
- Perform source-to-target mapping and technical data analysis.
- Implement pipeline logging, monitoring, exception handling, and recovery mechanisms.
Database & Platform Engineering
- Design and optimize relational database schemas and data structures.
- Analyze and improve SQL/query performance.
- Support indexing, partitioning, storage optimization, and database performance.
- Implement appropriate database security and access controls.
- Support database monitoring, availability, backup/recovery, and operational requirements in collaboration with infrastructure/platform teams.
- Troubleshoot database and pipeline performance issues.
- Contribute to cloud data-platform configuration and optimization.
Data Quality
- Implement automated validation and data-quality controls.
- Develop reconciliation processes between source and target systems.
- Identify duplicate, incomplete, inconsistent, and invalid data.
- Implement cleansing, standardization, validation, and exception-management logic.
- Work with technical and business stakeholders to understand and implement business data rules.
Technical Delivery
- Convert technical designs into reliable production solutions.
- Participate in technical design and code reviews.
- Mentor junior/mid-level engineers.
- Support estimation and technical planning.
- Troubleshoot complex production and integration issues.
- Collaborate with technical leads, application teams, DevOps, QA, BI, and client teams.
- Document technical designs, mappings, configurations, operational procedures, and engineering decisions.
Consulting & AI-Led Working
- Understand the business purpose behind assigned engineering requirements.
- Raise risks, assumptions, dependencies, and potential improvements proactively.
- Communicate effectively with client and internal stakeholders.
- Use AI-assisted tools to improve coding, testing, analysis, documentation, and troubleshooting productivity.
- Independently verify AI-generated code and recommendations before implementation.
- Identify opportunities for engineering automation and process improvement.
Required Qualifications
- 6–9 years of experience in data engineering, database engineering, data integration, or related areas.
- Advanced SQL skills.
- Strong hands-on Python experience.
- Strong ETL/ELT development experience.
- Strong relational database knowledge, such as SQL Server, PostgreSQL, Oracle, or equivalent.
- Experience with data modeling and database design.
- Experience with AWS, Azure, or another major cloud platform.
- Experience with modern data technologies such as Databricks, Snowflake, Redshift, Synapse, Glue, ADF, Airflow, dbt, or equivalent.
- Experience with performance tuning and optimization.
- Experience with data validation and reconciliation.
- Strong troubleshooting and analytical skills.
- Ability to take ownership of engineering deliverables with limited supervision.
Preferred Qualifications
- Experience working with enterprise ERP, CRM, PIM, PLM, MES, or related systems.
- Experience with manufacturing, retail, distribution, or consumer-goods data.
- Experience with CI/CD and infrastructure/platform engineering practices.
- Experience with API and event-driven integrations.
- Previous consulting or technology-services experience.
What Success Looks Like
- Pipelines and databases perform reliably at enterprise scale.
- Engineering solutions are maintainable, reusable, and well documented.
- Data issues are detected and addressed systematically.
- Junior engineers receive effective technical guidance.
- Problems are owned through resolution rather than simply escalated.
- Engineering decisions reflect both technical requirements and client business objectives.
Data Architect – Databricks & AWS
- Strong experience in Data Architecture, Data Engineering, Databricks, Apache Spark/PySpark, Python, and Advanced SQL.
- Design and implement scalable ETL/ELT pipelines, data platforms, and Lakehouse architectures using Medallion Architecture.
- Experience with Databricks, Databricks Workflows, Unity Catalog OR Databricks Jobs
- Strong knowledge of Delta Lake, Databricks Workflows, Delta Live Tables (DLT), and dimensional data modeling.
- Hands-on experience with AWS services such as S3, Glue, IAM, Lambda, and CloudWatch.
- Experience with Apache Airflow, Data Warehouse concepts, Git/CI-CD, performance optimization, and data quality.
- Good to have exposure to Kafka/Structured Streaming, Unity Catalog, and modern data governance.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon