Data Engineer at Ganit Business Solutions · Chennai, Bengaluru (Bangalore), Mumbai · 4 - 6 years · ₹7L - ₹15L / yr · Bootstrapped · Posted 29 Jan 2022
Amazon Web Services (AWS)Responsibilities:
- Must be able to write quality code and build secure, highly available systems.
- Assemble large, complex datasets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing datadelivery, re-designing infrastructure for greater scalability, etc with the guidance.
- Create datatools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Monitoring performance and advising any necessary infrastructure changes.
- Defining dataretention policies.
- Implementing the ETL process and optimal data pipeline architecture
- Build analytics tools that utilize the datapipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Create design documents that describe the functionality, capacity, architecture, and process.
- Develop, test, and implement datasolutions based on finalized design documents.
- Work with dataand analytics experts to strive for greater functionality in our data
- Proactively identify potential production issues and recommend and implement solutions
Skillsets:
- Good understanding of optimal extraction, transformation, and loading of datafrom a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Proficient understanding of distributed computing principles
- Experience in working with batch processing/ real-time systems using various open-source technologies like NoSQL, Spark, Pig, Hive, Apache Airflow.
- Implemented complex projects dealing with the considerable datasize (PB).
- Optimization techniques (performance, scalability, monitoring, etc.)
- Experience with integration of datafrom multiple data sources
- Experience with NoSQL databases, such as HBase, Cassandra, MongoDB, etc.,
- Knowledge of various ETL techniques and frameworks, such as Flume
- Experience with various messaging systems, such as Kafka or RabbitMQ
- Good understanding of Lambda Architecture, along with its advantages and drawbacks
- Creation of DAGs for dataengineering
- Expert at Python /Scala programming, especially for dataengineering/ ETL purposes
Shubham Vishwakarma
Full Stack Developer - Averlon
About Ganit Business Solutions
About
Ganit Inc. is in the business of enhancing the Decision Making Power (DMP) of businesses by offering solutions that lie at the crossroads of discovery-based artificial intelligence, hypothesis-based analytics, and the Internet of Things (IoT).
The company's offerings consist of a functioning product suite and a bespoke service offering as its solutions. The goal is to integrate these solutions into the core of their client's decision-making processes as seamlessly as possible. Customers in the FMCG/CPG, Retail, Logistics, Hospitality, Media, Insurance, and Banking sectors are served by Ganit's offices in both India and the United States. The company views data as a strategic resource that may assist other businesses in achieving growth in both their top and bottom lines of business. We build and implement AI and ML solutions that are purpose-built for certain sectors to increase decision velocity and decrease decision risk.
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PythonJob Summary
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We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.
Experience with Google Cloud Platform (GCP) will be an added advantage.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
- Develop complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain reliable data integration workflows across multiple data sources.
- Perform data cleansing, validation, transformation, and quality checks.
- Analyze data and provide insights to support business and technical requirements.
- Implement and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
- Troubleshoot data pipeline failures, performance issues, and production incidents.
- Optimize data processing workflows for performance, scalability, and reliability.
- Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
- Follow best practices for version control, testing, documentation, and deployment.
- Contribute to cloud-based data engineering initiatives, preferably on GCP.
Required Skills
- 5–7 years of hands-on experience in Data Engineering.
- Strong programming skills in Python.
- Strong expertise in Advanced SQL and database concepts.
- Hands-on experience with ETL/ELT processes and data pipelines.
- Good understanding of Data Warehousing and Data Modeling concepts.
- Experience with CI/CD practices and tools.
- Strong understanding of DevOps principles, automation, and deployment processes.
- Strong data analytics and problem-solving skills.
- Experience working with large datasets and performance optimization.
- Good understanding of Git/version control and software development best practices.
Good to Have
- Hands-on experience with Google Cloud Platform (GCP).
- Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
- Experience with containerization/orchestration technologies such as Docker/Kubernetes.
- Experience with workflow orchestration tools such as Airflow.
- Knowledge of cloud-based data architecture and distributed data processing.
Preferred Candidate Profile
- Strong analytical and problem-solving abilities.
- Good communication and stakeholder management skills.
- Ability to work independently as well as in a collaborative team environment.
- Strong ownership of data pipelines and production systems.
- Candidates who can join at short notice are preferred.
Mandatory Skills
Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops
Python
ScalaDescription
We are looking for Senior Data Engineers to join our Data Platform team and build scalable, high-performance data platforms that power data processing, analytics, and downstream applications.
The ideal candidate will have strong experience in distributed data processing, ETL pipelines, and Big Data technologies, with hands-on expertise in Apache Spark and Python Scala.
You will be responsible for designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL and data processing pipelines for large-scale datasets.
- Build and optimize distributed data applications using Apache Spark and Python Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Design and manage data workflows using Apache Airflow.
- Build and operate data workloads on AWS, with strong usage of Amazon S3 for large-scale data storage.
- Work with large datasets to ensure data quality, consistency, reliability, and performance.
- Collaborate with engineering, product, analytics, and other platform teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, performance, and cost efficiency.
- Troubleshoot production issues, identify bottlenecks, and continuously improve platform performance.
Requirements
Candidates who demonstrate:
- 5+ years of experience in Data Engineering, Big Data Engineering, or a similar role.
- Strong hands-on experience with Apache Spark and Scala.
- Experience designing, building, and maintaining large-scale ETL pipelines.
- Strong hands-on experience with AWS, particularly Amazon S3.
- Hands-on experience with Apache Airflow for workflow orchestration and scheduling.
- Strong SQL skills and a solid understanding of distributed data processing concepts.
- Experience working with batch and/or streaming data pipelines.
- Excellent debugging, problem-solving, and performance optimization skills.
- Strong communication and collaboration skills.
Good to Have
- Experience with Databricks and the broader Databricks data platform.
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- Experience working on large-scale data platforms handling high-volume data workloads.
- Exposure to additional AWS data services and cloud-native data architectures.
PythonJob Description
We are looking for an experienced Data Engineer with strong expertise in Python, ETL, SQL, CI/CD, and DevOps to design, develop, and maintain scalable data pipelines and data processing solutions.
Key Responsibilities
- Design, develop, and maintain scalable ETL/ELT data pipelines.
- Develop data processing solutions using Python.
- Write complex and optimized SQL queries, stored procedures, and data transformations.
- Build and maintain data ingestion and integration workflows.
- Implement data quality, validation, monitoring, and error-handling processes.
- Develop and maintain CI/CD pipelines for data engineering applications.
- Work with DevOps tools and practices for automated build, deployment, and infrastructure management.
- Collaborate with data analysts, data scientists, software engineers, and business teams.
- Optimize data pipelines for performance, reliability, and scalability.
- Troubleshoot production data issues and ensure timely resolution.
- Follow best practices for version control, code quality, testing, and deployment.
Mandatory Skills
- Python
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- SQL
- CI/CD
- DevOps
- Git / Version Control
- Strong problem-solving and debugging skills
PythonJob Summary
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.
Key Responsibilities
- Design, develop, and maintain ETL/ELT data pipelines.
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- Work with Linux environments for deployment, monitoring, and troubleshooting.
- Ensure data quality, integrity, and reliability across data platforms.
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Required Skills
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- Familiarity with Git/version control.
- Strong analytical and problem-solving skills.
Preferred Skills
- Experience with cloud platforms (AWS, Azure, or GCP).
- Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
- Experience with data warehousing solutions and big data technologies.
- Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Relevant certifications in cloud or data engineering are an added advantage.
PythonData Engineer Short Hiring Post
🚨 Hiring: Data Engineer
🔹 Experience: 5–9 Years
🔹 Location: Bangalore / Hyderabad
🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling
🔹 Process: L1 Virtual → L2 F2F Karat Test
🔹 F2F: Bangalore / Hyderabad Location
🔹 Positions: Immediate requirement
⚠️ Note: Candidates must be available for F2F Karat immediately after L1.
#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners
PythonAmazon Web Services (AWS)About Us:
The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.
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- Expertise in SQL, including developing stored procedures (SP) and applying advanced data design concepts.
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- Experience with AWS or Azure services (e.g., AWS Glue, Azure Data Factory, Redshift, Snowflake).
- Familiarity with big data tools such as Apache Kafka, Apache Spark, or Flink.
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- Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
- Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
- Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
- Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
- Work on impactful projects that make a difference across industries.
- Opportunities for professional growth and continuous learning.
- Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX Impact team!
KubernetesScalaDescription
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You will work on designing, developing, and optimizing large-scale data pipelines while collaborating closely with cross-functional engineering teams to build reliable, production-grade data solutions.
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- Design, develop, and maintain scalable ETL pipelines for large-scale data processing.
- Build and optimize distributed data applications using Spark and Scala.
- Develop reliable, high-performance data pipelines for batch and streaming workloads.
- Work with large datasets to ensure data quality, consistency, and performance.
- Collaborate with engineering, product, and analytics teams to deliver robust data solutions.
- Optimize data workflows for scalability, reliability, and cost efficiency.
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- Strong communication and collaboration skills.
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Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.
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Dear Candidate,
Thanks for showing interest in the opportunity!!!
As discussed, we have an opening for ETL Developer – Hadoop & PySpark with Mphasis for the Bangalore location – Permanent.
Job Description:
We are looking for an experienced ETL Developer with strong expertise in ETL development, Hadoop, and PySpark. The candidate should have hands-on experience in data processing, building and maintaining ETL pipelines, data transformation, and handling large datasets using Big Data technologies.
Primary & Mandatory Skills:
- ETL Development
- Hadoop / HDFS
- PySpark / Apache Spark
- Data Extraction, Transformation & Loading
- SQL and Data Processing
Good to Have:
- Hive / Spark SQL
- Data Pipeline Development
- Big Data Processing
- Python Programming
Company: Mphasis
Role: ETL Developer – Hadoop & PySpark
Experience: As per requirement
Location: Bangalore
Employment Type: Permanent
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PythonUrgent Hiring – Senior Data Engineer
We are hiring for a Senior Data Engineer for a reputed product-based company in Pune.
Location: Pune – Magarpatta / Baner
Experience: 7–10 Years
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Notice Period: Immediate to 30 Days preferred
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- 4+ years of experience in Snowflake
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- Experience with Airflow or equivalent orchestration tools
- Strong experience in ETL/ELT and Data Pipelines
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- Exposure to dbt or similar transformation tools
- Experience in data pipeline monitoring, troubleshooting and performance optimization
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- Exposure to large-scale data platforms and business-critical data solutions
- Collaborative and technically strong environment
Interested candidates can share their updated CV for immediate consideration.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon